Methods of diagnosing and treating patients with cutaneous squamous cell carcinoma

ABSTRACT

The present disclosure relates to methods for predicting the risk of recurrence and/or metastasis, or both in primary cutaneous squamous cell carcinoma (cSCC).

FIELD OF THE DISCLOSURE

The present disclosure relates to methods for predicting the risk ofrecurrence and/or metastasis in primary cutaneous squamous cellcarcinoma (cSCC).

BACKGROUND

Cutaneous squamous cell carcinoma (cSCC) is rivaled only by basal cellcarcinoma as the most common cancer in the U.S. Though most cases arecured by excision, a subset recur and become incurable with the numberof deaths approximating melanoma (Karia et al., J. Am. Acad. Dermatol.68(6): 957-66 (2013)). Despite overall good prognosis for patients withcSCC, a subset will develop local, regional, or distantrecurrences/metastases following complete excision of the primary tumor.Those at high risk of recurrence are eligible for adjuvant treatmentoptions. While specific clinical and pathologic features are associatedwith recurrence, they collectively fail to identify 30-40% of all cSCCrecurrences and many tumors that possess high risk features will notrecur. Furthermore, the rates of metastasis in high-risk patients (e.g.,immunocompromised) and those diagnosed with tumors with high-riskfeatures can exceed 20%. Once metastasis is detected, survival rates arepoor. Prediction models with increased positive predictive values whilemaintaining high negative predictive values are needed to accuratelyidentify patients with high-risk features who are at a much higher riskof developing metastasis and dying from cSCC than the high-risk featuresalone suggest. Prediction models with increased positive predictivevalues while maintaining high negative predictive values are criticaland may allow for early intervention with adjuvant therapies. Similarly,many patients with high-risk features do not have recurrences and thusmaintaining a high negative predictive value is important to avoidovertreatment and prevent unnecessary procedures in patients with lowrisk cSCC that are mis-categorized as high risk cSCC when using clinicaland pathologic features alone. Patients with high-risk features but whoare at an actual low risk of metastasis can avoid overtreatment of lowrisk tumors. To address the need for more accurate predictive factorsand facilitate appropriate intervention strategies, gene expressionanalysis was used to determine a signature associated with recurrence inpatients with cSCC.

SUMMARY

There is a need in the art for a more objective method of predictingwhich tumors display aggressive recurrence/metastatic activity.Development of an accurate molecular footprint, such as the geneexpression profile assay disclosed herein, would be a significantadvance forward for the field. A multi-center study using archivedprimary tissue samples with extensive capture of associated clinical andpathologic data (subjects with pathologically confirmed cSCC, minimum 2years of follow-up, and two separate outcome measures: nodal/distantmetastasis and local recurrence) was used to identify a 40-geneexpression profile (40-GEP) test that accurately predicts primary cSCCwith a high risk of metastasis, and primary cSCC with high risk ofrecurrence after complete surgical clearance. In particular, the 40-GEPtest disclosed herein identifies three classes (Class 1, Class 2A, andClass 2B) of cSCC patients who have increased likelihood of developingnodal or distant metastasis within 3 years of diagnosis. The 40-GEP testis an independent predictor of patient outcomes and improves upon riskprediction with American Joint Committee on Cancer (AJCC), BrighamWomen's Hospital (BWH), and National Comprehensive Cancer Network (NCCN)systems supporting its clinical use in conjunction with or independentof standard staging and patient management criteria.

In one embodiment, a method for treating a patient with a cutaneoussquamous cell carcinoma (cSCC) tumor is disclosed herein, the methodcomprising: (a) obtaining a diagnosis identifying a risk of metastasis,in a cSCC tumor sample from the patient, wherein the diagnosis wasobtained by: (1) determining the expression level of 34 genes in a geneset; wherein the 34 genes in the gene set are: ACSBG1, ALOX12, APOBEC3G,ATP6VOE2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1(ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC,PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L,TFAP2B, ZNF48, ZNF496, and ZNF839; (2) comparing the expression levelsof the 34 genes in the gene set from the cSCC tumor sample to theexpression levels of the 34 genes in the gene set from a predictivetraining set to generate a probability score of the risk of metastasis,and; (3) providing an indication as to whether the cSCC tumor has a lowrisk to a high risk of metastasis, based on the probability scoregenerated in step (2); and (4) identifying that the cSCC tumor has ahigh risk of metastasis, based on the probability score and diagnosingthe cSCC tumor as having a high risk of metastasis; (b) administering tothe patient an aggressive treatment when the determination is made inthe affirmative that the patient has a cSCC tumor with a high risk ofmetastasis. In certain embodiments, the method further comprisesperforming a resection of the cSCC tumor when the determination is madein the affirmative that the patient has a cSCC tumor with a high risk ofmetastasis.

In some embodiments, the expression level of each gene in the gene setis determined by reverse transcribing the isolated mRNA into cDNA andmeasuring a level of fluorescence for each gene in the gene set by anucleic acid sequence detection system following Real-Time PolymeraseChain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sampleis obtained from formalin-fixed, paraffin embedded sample.

In another embodiment, the gene set comprises at least one additionalgene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1,C1QL4, C21orf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10, CXCR4,CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1, EGFR, EphB2, FCHSD1,FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24, IL2RB,IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR,LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13, MMP3, MMP7,MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3,PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9,SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM41B,TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/orZSCAN31. In other embodiments, the gene set comprises an additional 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40genes selected from the genes listed above.

In another embodiment, a method of treating a patient with a cutaneoussquamous cell carcinoma (cSCC) tumor is disclosed herein, the methodcomprising administering an aggressive cancer treatment regimen to thepatient, wherein the patient has a cSCC tumor with a moderate risk(Class 2A) or a high risk (Class 2B) as generated by comparing theexpression levels of 34 genes selected from ACSBG1, ALOX12, APOBEC3G,ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1(ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC,PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L,TFAP2B, ZNF48, ZNF496, and ZNF839 from the cSCC tumor with theexpression levels of the same 34 genes selected from ACSBG1, ALOX12,APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2,LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4,NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1,TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839 from a predictive training set.In one embodiment, the cSCC tumor is determined to have a low risk(Class 1), a moderate risk (Class 2A), or a high risk (Class 2B),wherein a patient having a low risk (Class 1) cSCC tumor has about a0-10% risk for metastasis, a patient having a moderate risk (Class 2A)cSCC tumor has about a 10-49% risk for metastasis, and a patient havinga high risk (Class 2B) cSCC tumor has about a 50-100% risk formetastasis.

In another embodiment, the gene set comprises at least one additionalgene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1,C1QL4, C21orf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10, CXCR4,CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1, EGFR, EphB2, FCHSD1,FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24, IL2RB,IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR,LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13, MMP3, MMP7,MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3,PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9,SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM41B,TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/orZSCAN31. In other embodiments, the gene set comprises an additional 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40genes selected from the genes listed above.

In another embodiment, a kit comprising primer pairs suitable for thedetection and quantification of nucleic acid expression of 34 genes isdisclosed herein, wherein the 34 genes are selected from: ACSBG1,ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3,ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1,MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3,SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839.

In some embodiments, the primer pairs suitable for the detection andquantification of nucleic acid expression of 34 genes are primer pairsfor: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8,GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502,MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135,RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839. Inother embodiments, the primer pairs comprise primer pairs for at leastone additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1,BLOC1S1, C1QL4, C21orf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10,CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1, EGFR, EphB2,FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24,IL2RB, IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B,LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13,MMP3, MMP7, MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1,PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8,S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1,TMEM41B, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6,and/or ZSCAN31. In other embodiments, the gene set comprises anadditional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, ormore than 40 genes selected from the genes listed above.

In another embodiment, a method for predicting risk of metastasis, in apatient with a cutaneous squamous cell carcinoma (cSCC) tumor isdisclosed herein, the method comprising: (a) obtaining a cSCC tumorsample from the patient and isolating mRNA from the sample; (b)determining the expression level of 34 genes in a gene set; wherein the34 genes in the gene set are selected from: ACSBG1, ALOX12, APOBEC3G,ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1(ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC,PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L,TFAP2B, ZNF48, ZNF496, and ZNF839; (c) comparing the expression levelsof the 34 genes in the gene set from the cSCC tumor sample to theexpression levels of the 34 genes in the gene set from a predictivetraining set to generate a probability score of the risk of metastasis;and (d) providing an indication as to whether the cSCC tumor has a lowrisk to a high risk of metastasis, based on the probability scoregenerated in step (c).

In some embodiments, the expression level of each gene in the gene setis determined by reverse transcribing the isolated mRNA into cDNA andmeasuring a level of fluorescence for each gene in the gene set by anucleic acid sequence detection system following Real-Time PolymeraseChain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sampleis obtained from formalin-fixed, paraffin embedded sample. In oneembodiment, the method further comprises identifying the cSCC tumor ashaving a high risk of metastasis, based on the probability score, andadministering to the patient an aggressive tumor treatment.

In another embodiment, the gene set comprises at least one additionalgene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1,C1QL4, C21orf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10, CXCR4,CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1, EGFR, EphB2, FCHSD1,FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24, IL2RB,IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR,LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13, MMP3, MMP7,MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3,PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9,SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM41B,TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/orZSCAN31. In other embodiments, the gene set comprises an additional 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40genes selected from the genes listed above.

In another embodiment, a method for predicting risk of metastasis, in apatient with a cutaneous squamous cell carcinoma (cSCC) tumor isdisclosed herein, the method comprising: (a) obtaining a cSCC tumorsample from the patient and isolating mRNA from the sample; (b)determining the expression level of 34 genes in a gene set; wherein the34 genes in the gene set are selected from: ACSBG1, ALOX12, APOBEC3G,ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1(ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC,PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L,TFAP2B, ZNF48, ZNF496, and ZNF839; and (c) providing an indication as towhether the cSCC tumor has a low risk to a high risk of metastasis,based on the expression level of 34 genes generated in step (b).

In some embodiments, the expression level of each gene in the gene setis determined by reverse transcribing the isolated mRNA into cDNA andmeasuring a level of fluorescence for each gene in the gene set by anucleic acid sequence detection system following Real-Time PolymeraseChain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sampleis obtained from formalin-fixed, paraffin embedded sample.

In another embodiment, the gene set comprises at least one additionalgene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1,C1QL4, C21orf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10, CXCR4,CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1, EGFR, EphB2, FCHSD1,FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24, IL2RB,IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR,LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13, MMP3, MMP7,MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3,PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9,SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM41B,TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/orZSCAN31. In other embodiments, the gene set comprises an additional 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40genes selected from the genes listed above.

In certain embodiments, the expression level of: ACSBG1 is decreased,ALOX12 is decreased, APOBEC3G is increased, ATP6V0E2 is increased, BBC3is increased, BHLHB9 is decreased, CEP76 is decreased, DUXAP8 isincreased, GTPBP2 is decreased, HDDC3 is increased, ID2 is decreased,LCE2B is decreased, LIME1 (ZGPAT) is increased, LOC100287896 isincreased, LOC101927502 is increased, MMP10 is decreased, MRC1 isdecreased, MSANTD4 is decreased, NFASC is decreased, NFIC is decreased,PDPN is increased, PI3 is decreased, PLS3 is decreased, RCHY1 isincreased, RNF135 is increased, RPP38 is decreased, RUNX3 is increased,SLC1A3 is increased, SPP1 is increased, TAF6L is increased, TFAP2B isdecreased, ZNF48 is increased, ZNF496 is increased, and ZNF839 isincreased when comparing a recurrent tumor to a non-recurrent sample.

In certain embodiments, the expression level of the at least oneadditional gene: ACSBG1 is decreased, AIM2 is increased, ALOX12 isdecreased, ANXA9 is decreased, APOBEC3G is increased, ARPC2 isdecreased, ATP6AP1 is decreased, ATP6V0E2 is increased, BBC isincreased, BHLHB9 is decreased, BLOC1S1 is decreased, C1QL4 isincreased, C21orf59 is increased, C3orf70 is increased, CCL27 isdecreased, CD163 is increased, CEP76 is decreased, CHI3L1 is increased,CHMP2B is decreased, CXCL10 is decreased, CXCR4 is increased, CYP2D6(LOC101929829) is decreased, DARS is decreased, DCT is decreased, DDAH1is decreased, DSS1 is decreased, DUXAP8 is increased, EGFR is increased,EphB2 is increased, FCHSD1 is decreased, FDFT1 is decreased, FLG isdecreased, FN1 is increased, GTPBP2 is decreased, HDDC3 is increased,HNRNPL is decreased, HOXA10 (HOXA9, MIR196B) is decreased, HPGD isdecreased, ID2 is decreased, IL24 is increased, IL2RB is decreased, IL7Ris increased, INHBA is increased, IPO5P1 is increased, KIT is increased,KLK5 is decreased, KRT17 is decreased, KRT18 is increased, KRT19 isdecreased, KRT6B is decreased, LAMC2 is decreased, LCE2B is decreased,LIME1 (ZGPAT) is increased, LOC100287896 is increased, LOC101927502 isincreased, LOR is decreased, LRRC47 is increased, MIER2 is increased,MIR129-1 is increased, MIR3916 is increased, MKLN1 is increased, MMP1 isincreased, MMP10 is decreased, MMP12 is increased, MMP13 is increased,MMP3 is increased, MMP7 is increased, MMP9 is decreased, MRC1 isdecreased, MRPL21 is increased, MSANTD4 is decreased, MYC is decreased,NEB is decreased, NEFL is decreased, NFASC is decreased, NFIA isdecreased, NFIB is decreased, NFIC is decreased, NOA1 is increased, PD1is decreased, PDL1 is increased, PDPN is increased, PI3 is decreased,PIG3 is decreased, PIGBOS1 is increased, PIM2 is increased, PLAU isincreased, PLS3 is decreased, PTHLH is decreased, PTRHD1 is decreased,RBM33 is increased, RCHY1 is increased, RNF135 is increased, RPL26L1 isincreased, RPP38 is decreased, RUNX3 is increased, S100A8 is decreased,S100A9 is decreased, SEPT3 is decreased, SERPINB2 is decreased, SERPINB4is decreased, SLC1A3 is increased, SLC25A11 is increased, SNORD124 isincreased, SPATA41 is increased, SPP1 is increased, TAF6L is increased,TFAP2B is decreased, THYN1 is increased, TMEM41B is decreased, TNNC1 isdecreased, TUBB3 is decreased, TUFM (MIR4721) is increased, TYRP1 isdecreased, UGP2 is decreased, USP7 is decreased, VIM is increased, YKT6is increased, ZNF48 is increased, ZNF496 is increased, ZNF839 isincreased, and/or ZSCAN31 is decreased. In certain embodiments, theincrease or decrease in the expression level is the gene level from arecurrent tumor sample versus a non-recurrent tumor sample. In otherembodiments, the increase or decrease in the expression level is thegene level from a metastatic tumor sample versus a non-metastatic tumorsample.

In another embodiment, a method for treating a patient with cutaneoussquamous cell carcinoma (cSCC) tumor is disclosed herein, the methodcomprising: (a) obtaining a cSCC tumor sample from the patient andisolating mRNA from the sample; (b) determining the expression level of34 genes in a gene set; wherein the 34 genes in the gene set areselected from: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76,DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896,LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1,RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, andZNF839; (c) providing an indication as to whether the cSCC tumor has alow risk (Class 1), a moderate risk (Class 2A), or a high risk (Class2B) of metastasis, based on the expression level of the 34 genesgenerated in step (b); and (d) administering to the patient anaggressive treatment when the determination is made in the affirmativethat the patient has a cSCC tumor with a moderate risk or a high risk ofmetastasis.

In some embodiments, the expression level of each gene in the gene setis determined by reverse transcribing the isolated mRNA into cDNA andmeasuring a level of fluorescence for each gene in the gene set by anucleic acid sequence detection system following Real-Time PolymeraseChain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sampleis obtained from formalin-fixed, paraffin embedded sample.

In another embodiment, the gene set comprises at least one additionalgene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1,C1QL4, C21orf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10, CXCR4,CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1, EGFR, EphB2, FCHSD1,FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24, IL2RB,IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR,LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13, MMP3, MMP7,MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3,PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9,SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM41B,TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/orZSCAN31. In other embodiments, the gene set comprises an additional 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40genes selected from the genes listed above.

In another embodiment, the disclosure provides a method of determiningone or more treatment options for a patient with a cutaneous squamouscell carcinoma (cSCC) tumor, the method comprising:

-   -   (a) identifying a risk of metastasis in a cSCC tumor sample from        the patient, wherein the risk of metastasis was identified by:        -   (1) determining the expression level of 34 genes in a gene            set; wherein the 34 genes in the gene set are:            -   ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76,                DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT),                LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC,                NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3,                SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839;        -   (2) comparing the expression levels of the 34 genes in the            gene set from the cSCC tumor sample to the expression levels            of the 34 genes in the gene set from a predictive training            set to identify the risk of metastasis and providing an            indication as to whether the cSCC tumor has a low risk            (Class 1), a moderate risk (Class 2A), or a high risk (Class            2B) of metastasis; and    -   (b) determining that the patient receive a low intensity        treatment, a moderate intensity treatment, or a high intensity        treatment when the determination is made that the patient has a        cSCC tumor with a low risk (Class 1), a moderate risk (Class        2A), or a high risk (Class 2B) of metastasis, respectively.

In certain embodiments, the low intensity treatment comprises one ormore of:

-   -   (a) clinical follow-up of one to two times per year;    -   (b) reduced imaging or low frequency to no imaging;    -   (c) reduced nodal assessment; and/or    -   (d) no adjuvant treatment.

In other embodiments, the moderate intensity treatment comprises one ormore of:

-   -   (a) clinical follow-up of two to four times per year for about 3        years;    -   (b) baseline and annual nodal imaging for about 2 years;    -   (c) consider a nodal biopsy or a neck dissection; and/or    -   (d) consider an adjuvant treatment.

In some embodiments, the high intensity treatment comprises one or moreof:

-   -   (a) clinical follow-up of four to twelve times per year for        about 3 years;    -   (b) baseline and annual nodal imaging at least twice a year for        about 2 years;    -   (c) recommend a nodal biopsy or a neck dissection; and/or    -   (d) recommend an adjuvant treatment and/or a clinical trial.

In certain embodiments, the method further comprises performing aresection of the cSCC tumor when the determination is made in theaffirmative that the patient has a cSCC tumor with a moderate risk(Class 2A) or a high risk (Class 2B) of metastasis.

In some embodiments, the expression level of each gene in a gene set isdetermined by reverse transcribing the isolated mRNA and measuring alevel of fluorescence for each gene in the gene set by a nucleic acidsequence detection system following RT-PCR. In an embodiment, the cSCCtumor sample is obtained from a formalin-fixed, paraffin embeddedsample.

In certain embodiments, the gene set further comprises at least onecontrol gene, wherein the at least one control gene is selected from thegroup consisting of BAG6, KMT2D/MLL2, MDM2, FXR1, KMT2C, MDM4, VIM, andNF1B. In an embodiment, the control genes are MDM2, KMT2D, BAG6, FXR1,MDM4, and KMT2C.

Other aspects, embodiments, and implementations will become apparentfrom the following detailed description and claims, with reference,where appropriate, to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows the study design workflow.

FIG. 2 shows the differential expression of 18 genes found to besignificantly differentially expressed between recurrent (Rec) andnon-recurrent (NR) cSCC cases

FIG. 3 shows another exemplary study design workflow.

FIG. 4 shows a metastasis-free survival curve (regional and distantmetastasis) for low risk, Class 1, and high-risk, Class 2, tumors usingthe 20-1 gene set.

FIG. 5 shows the study cohorts: tissue samples and associated dataacquisition. Abbreviations: CRF, case report form; f/u, follow up;event, regional or distant metastasis; QC, quality control.

FIG. 6 shows the Kaplan-Meier analysis of the 40-GEP prognostic test andoutcomes from independent validation of cutaneous SCC cases (n=321).

FIG. 7 shows the demographics and clinical characteristics of validationcohort (n=321). Data analyzed using Chi-square test or Kruskal-Wallis Ftest. Abbreviations: Hx, history; SCC, squamous cell carcinoma; H&N,head and neck; StDev, standard deviation; PNI, perineural invasion; MMS,Mohs micrographic surgery; AJCC8, American Joint Committee on Cancer,Cancer Staging Manual, Eighth Edition; BWH, Brigham and Women'sHospital; NCCN, National Comprehensive Cancer Network. *One (n=1)patient did not report ethnicity. **Tumor diameter reported (n=295).#Tumor thickness reported (n=115). ##Mohs or wide local excision (n=319)with 2 cases not having additional surgery beyond biopsy.

FIG. 8 shows Multivariate Cox regression analyses of risk for metastasisin 40-GEP validation cases (n=321) with binary AJCC and BWH T stage. Anevent was regional or distant metastasis. Abbreviations: HR, hazardratio; CI, confidence interval; GEP, gene expression profile; AJCC8,American Joint Committee on Cancer, Cancer Staging Manual, EighthEdition; BWH, Brigham and Women's Hospital.

FIG. 9 shows classification of cases by 40-GEP Class andclinicopathologic risk group (n=321).

FIG. 10 shows the accuracy of risk prediction of the 40-GEP and riskassessment methods (n=321).

FIG. 11 shows Multivariate Cox regression analyses of risk formetastasis in 40-GEP validation cases (n=321) with AJCC or BWH T stage.

FIG. 12 shows the demographics of the training cohort.

FIG. 13 shows Multivariate Cox regression analyses for risk ofmetastasis in validation cases with individual pre-operative andpost-operative features.

FIG. 14A-14B show the application of 40-GEP test results and T stage toNCCN-defined levels of risk for improving risk-appropriate management ofcSCC. FIG. 14A—Using a cohort (n=300) of clinicopathologically definedcSCC patients meeting study criteria and who were NCCN-defined highrisk, the 40-GEP test stratified the patients into three groupsdepending on risk for metastasis at 3 years post-diagnosis: low (Class1, n=189), high (Class 2A, n=87), or highest (Class 2B, n=24). Patientsstratified as Class 1, 2A, and 2B had a 9%, 21%, and 63% risk formetastasis, respectively, per the 40-GEP test alone. Corresponding AJCCand BWH T stages and metastasis rates were analyzed. FIG.14B—Incorporation of 40-GEP Class plus AJCC and BWH T stages into threemetastasis risk bins (<10%, 10-50%, and >50% risk) resulted in low,moderate, and high intensity management strategies. The 40-GEPintegration demonstrates low management intensity for 53.0% (AJCC) or57.7% (BWH), high intensity management for 8.0%, and moderate intensitymanagement for the remainder (39.0%, AJCC; 34.3%, BWH) of the300-patient cohort.

FIG. 15 shows an exemplary recommended risk-aligned cSCC patientmanagement for prognostic groups based on 40-GEP and T stage. *Risk formetastasis is reported for 40-GEP Class and AJCC T stage.

FIG. 16 shows the characteristics of the NCCN high-risk cSCC cohort(n=300).

DETAILED DESCRIPTION

Despite overall good prognosis for patients with cSCC, a subset willdevelop metastasis (i.e., local, regional, or distant recurrences, orany combination) following complete excision of the primary tumor. Thoseat high risk of metastasis/recurrence are eligible for adjuvanttreatment options. While specific clinical features are associated withmetastasis/recurrence, they collectively fail to identify 30-40% of allcSCC recurrences and many tumors that express high risk features willnot recur. To address the need for more accurate predictive factors andfacilitate appropriate intervention strategies, a gene expressionanalysis was used to determine a signature associated withmetastasis/recurrence in cSCC. In that analysis, 140 candidate geneswere selected for evaluation of gene expression changes in recurrent(metastatic) and non-recurrent cases. A total of 230 primary cSCC tumorswere collected under an IRB-approved, multi-center protocol andanalyzed. After quality filtering, expression of the genes was assessedacross 202 samples. Multiple subsets of genes were significantlydifferentially expressed between metastatic/recurrent and non-recurrentcases. The results demonstrate that gene expression differences candistinguish between metastatic/recurrent and non-recurrent cSCC. Suchgene expression differences can help identify those patients who mightbenefit from additional therapeutic interventions and treatments.

Unless otherwise defined, all technical and scientific terms used hereinhave the same meaning as would be commonly understood by one of ordinaryskill in the art to which the claimed invention belongs. Althoughmethods and materials similar or equivalent to those described hereincan be used to practice the methods and kits disclosed or claimedherein, suitable methods and materials are described below. Allpublications, patent applications, patents, and other referencesmentioned herein are incorporated by reference in their entirety. Incase of conflict, the present specification, including definitions, willcontrol. In addition, the materials, methods, and examples areillustrative only and are not intended to be limiting. Other featuresand advantages of the claimed invention will be apparent from thefollowing detailed description.

As used herein, the singular forms “a,” “an,” and “the” include pluralreferents unless the context clearly dictates otherwise. For example,reference to “a nucleic acid” means one or more nucleic acids.

It is noted that terms like “preferably,” “commonly,” and “typically”are not utilized herein to limit the scope of the claimed invention orto imply that certain features are critical, essential, or evenimportant to the structure or function of the claimed invention. Rather,these terms are merely intended to highlight alternative or additionalfeatures that can or cannot be utilized in a particular embodimentdisclosed or claimed herein.

As used herein, the terms “polynucleotide,” “nucleotide,”“oligonucleotide,” and “nucleic acid” can be used interchangeably torefer to nucleic acid comprising DNA, cDNA, RNA, derivatives thereof, orcombinations thereof.

In an embodiment, a method for treating a patient with a cutaneoussquamous cell carcinoma (cSCC) tumor is disclosed herein, the methodcomprising: (a) obtaining a diagnosis identifying a risk of localmetastasis (i.e., recurrence, regional metastasis, distant metastasis,or any combination), in a cSCC tumor sample from the patient, whereinthe diagnosis was obtained by: (1) determining the expression level of34 genes in a gene set; wherein the 34 genes in the gene set areselected from: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76,DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896,LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1,RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, andZNF839; (2) comparing the expression levels of the 34 genes in the geneset from the cSCC tumor sample to the expression levels of the 34 genesin the gene set from a predictive training set to generate a probabilityscore of the risk of metastasis, and; (3) providing an indication as towhether the cSCC tumor has a low risk to a high risk of metastasis,based on the probability score generated in step (2); and (4)identifying that the cSCC tumor has a high risk of metastasis, based onthe probability score and diagnosing the cSCC tumor as having a highrisk of metastasis; (b) administering to the patient an aggressivetreatment when the determination is made in the affirmative that thepatient has a cSCC tumor with a high risk of metastasis. In certainembodiments, the method further comprises performing a resection of thecSCC tumor when the determination is made in the affirmative that thepatient has a cSCC tumor with a high risk of metastasis.

In some embodiments, the expression level of each gene in the gene setis determined by reverse transcribing the isolated mRNA into cDNA andmeasuring a level of fluorescence for each gene in the gene set by anucleic acid sequence detection system following Real-Time PolymeraseChain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sampleis obtained from formalin-fixed, paraffin embedded sample.

In another embodiment, the gene set comprises at least one additionalgene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1,C1QL4, C21orf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10, CXCR4,CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1, EGFR, EphB2, FCHSD1,FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24, IL2RB,IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR,LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13, MMP3, MMP7,MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3,PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9,SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM41B,TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/orZSCAN31. In other embodiments, the gene set comprises an additional 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40genes selected from the genes listed above.

In an embodiment, a method of treating a patient with a cutaneoussquamous cell carcinoma (cSCC) tumor is disclosed herein, the methodcomprising administering an aggressive cancer treatment regimen to thepatient, wherein the patient has a cSCC tumor with moderate risk (Class2A), or a high risk (Class 2B) as generated by comparing the expressionlevels of 34 genes selected from ACSBG1, ALOX12, APOBEC3G, ATP6V0E2,BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT),LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN,PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B,ZNF48, ZNF496, and ZNF839 from the cSCC tumor with the expression levelsof the same 34 genes selected from ACSBG1, ALOX12, APOBEC3G, ATP6V0E2,BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT),LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN,PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B,ZNF48, ZNF496, and ZNF839 from a predictive training set. In oneembodiment, the cSCC tumor is determined to have a low risk (Class 1), amoderate risk (Class 2A), or a high risk (Class 2B), wherein a patienthaving a low risk (Class 1) cSCC tumor has about a 0-10% risk formetastasis, a patient having a moderate risk (Class 2A) cSCC tumor hasabout a 10-49% risk for metastasis, and a patient having a high risk(Class 2B) cSCC tumor has about a 50-100% risk for metastasis (i.e.,local recurrence, regional metastasis, distant metastasis, or anycombination).

In another embodiment, the gene set comprises at least one additionalgene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1,C1QL4, C21orf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10, CXCR4,CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1, EGFR, EphB2, FCHSD1,FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24, IL2RB,IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR,LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13, MMP3, MMP7,MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3,PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9,SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM41B,TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/orZSCAN31. In other embodiments, the gene set comprises an additional 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40genes selected from the genes listed above.

As used herein, the terms “metastasis” and “recurrence” are usedinterchangeably, and refer to the recurrence or disease progression thatmay occur locally (such as local recurrence and in transit disease),regionally (such as regional metastasis, nodal micrometastasis ormacrometastasis), or distally (such as distal metastasis to brain, lungand/or other tissues). In certain embodiment, regional metastasis refersto a metastatic lesion within the regional nodal basin, includingsatellite or in-transit metastasis, but excluding local recurrence, anddistant metastasis refers to metastasis beyond the regional lymph nodebasin. Risk, as used herein, includes low-risk, moderate-risk, orhigh-risk of metastasis according to any of the statistical methodsdisclosed herein. In one embodiment, risk of recurrence or metastasisfor cSCC can be classified from a low risk to a high risk (for example,the cSCC tumor has a graduated risk from low risk to high risk or highrisk to low risk of metastasis, local recurrence, regional metastasis,or distant metastasis). In other embodiments, low risk refers to a3-year relapse-free survival rate, a 3-year metastasis free survivalrate, or a 3-year disease specific survival rate of greater than 50%,55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or more than 95%, and highrisk refers to a 3-year relapse-free survival rate, a 3-year metastasisfree survival rate, or a 3-year disease specific survival rate of lessthan 50%, 45%, 40%, 35%, 30%, 25%, 20%, 15%, 10%, 5%, or less than 5%.Class 1, Class 2A, or Class 2B risk of metastasis, as used herein,includes low-risk (Class 1; for example having a recurrence risk of lessthan 25%, 20%, 15%, 10%, 5%, or less than 5%), moderate risk (Class 2A;for example having a recurrence risk of 75%, 70%, 65%, 60%, 55%, 50%,45%, 40%, 35%, 30%, 25%, or any number in between) or high-risk (Class2B; for example, having a recurrence risk of 50, 75%, 80%, 85%, 90%,95%, or higher than 95%) of metastasis according to any of thestatistical methods disclosed herein. In certain embodiments, a low risk(Class 1) cSCC tumor has about a 0-10% risk for metastasis, a patienthaving a moderate risk (Class 2A) cSCC tumor has about a 10-49% risk formetastasis, and a patient having a high risk (Class 2B) cSCC tumor hasabout a 50-100% risk for metastasis.

In certain embodiments, risk stratifications may be binned, for examplea group with an arbitrary designation Class 1 may be selected based onrecurrence risk of less than 25%, 20%, 15%, 10%, 5%, or less than 5%. Agroup with arbitrary designation Class 2A may be selected based on arisk of 75%, 70%, 65%, 60%, 55%, 50%, 45%, 40%, 35%, 30%, 25%, or anynumber in between. A group with arbitrary designation Class 2B may beselected based on a risk of 75%, 80%, 85%, 90%, 95%, or higher than 95%.These Class designations may comprise more than three groups or as fewas two groups depending on the separation characteristics of thepredictive algorithm. A person familiar with the art will be able todetermine the optimal binning strategy depending on the distributions ofClass probability scores developed by modeling.

The term “distant metastasis” or “distal metastasis” as used herein,refers to metastases from a primary cSCC tumor that are disseminatedwidely. Patients with distant metastases require aggressive treatments,which can eradicate metastatic cSCC, prolong life, and/or cure somepatients. In certain embodiments, a low risk (Class 1) cSCC tumor hasabout a 0-10% risk for distant metastasis, a patient having a moderaterisk (Class 2A) cSCC tumor has about a 10-49% risk for distantmetastasis, and a patient having a high risk (Class 2B) cSCC tumor hasabout a 50-100% risk for distant metastasis.

As used herein, the terms “local metastasis” and “local recurrence” canbe used interchangeably and refer to cancer cells that have spread totissue immediately surrounding the primary cSCC tumor or were notcompletely ablated or removed by previous treatment or surgicalresection. Local recurrences are typically resistant to chemotherapy andradiation therapy. Local recurrence can be difficult to control and/ortreat if: (1) the primary cSCC tumor is located or involves a vitalorgan or structure that limits the potential for treatment; (2)recurrence after surgery or other therapy occurs, because while likelynot a result from metastasis, high rates of recurrence indicate anadvanced cSCC tumor; and (3) presence of lymph node metastases, whilerare in cSCC, indicate advanced disease.

In some embodiments, the methods described herein can comprisedetermining that the cSCC tumor has an increased risk of metastasis ordecreased overall survival by combining with clinical staging factorsrecommended by, for example, the American Joint Committee on Cancer(AJCC), the Brigham Women's Hospital (BWH), or the NationalComprehensive Cancer Network (NCCN), to stage the primary cSCC tumor, orother histological features associated with risk of cSCC tumormetastasis or disease-related death.

As used herein, the terms “cutaneous squamous cell carcinoma” or “cSCC”or “SCC” refer to any cutaneous squamous cell carcinoma, regardless oftumor size, in patients without clinical or histologic evidence ofregional or distant metastatic disease. A cutaneous squamous cellcarcinoma sample may be obtained through a variety of sampling methodssuch as punch biopsy, shave biopsy, surgical excision (including Mohsmicrographic surgery and wide local excision, or similar technique),core needle biopsy, incisional biopsy, endoscope ultrasound (EUS)guided-fine needle aspirate (FNA) biopsy, percutaneous biopsy, and othermeans of extracting RNA from the primary cSCC tumor. A carcinoma is atype of cancer that develops from epithelial cells. Specifically, acarcinoma is a cancer that begins in a tissue that lines the inner orouter surfaces of the body, and that arises from cells originating inthe endodermal, mesodermal, and ectodermal germ layer duringembryogenesis. Squamous cell carcinomas have observable features andcharacteristics indicative of squamous differentiation (e.g.,intercellular bridges, keratinization, squamous pearls). The mostrecognized risk factor for cSCC is exposure to sunlight; thus, most cSCCtumors develop on sun-exposed skin sites, for example, the head or neckarea. They can also be found on the face, ears, lips, trunk, arms, legs,hands, or feet. Squamous cell carcinoma is the second most common skincancer.

As used herein, “overall survival” (OS) refers to the percentage ofpeople in a study or treatment group who are still alive for a certainperiod of time after they were diagnosed with or started treatment for adisease, such as cancer. The overall survival rate for cSCC is oftenstated as a three-year survival rate, which is the percentage of peoplein a study or treatment group who are alive three years after theirdiagnosis or the start of treatment.

The phrase “measuring the gene-expression levels” or “determining thegene-expression levels,” as used herein, refers to determining orquantifying RNA or proteins expressed by the gene or genes. The term“RNA” includes mRNA transcripts, and/or specific spliced variants ofmRNA. The term “RNA product of the gene,” as used herein, refers to RNAtranscripts transcribed from the gene and/or specific spliced variants.In some embodiments, mRNA is converted to cDNA before the geneexpression levels are measured. With respect to proteins, geneexpression refers to proteins translated from the RNA transcriptstranscribed from the gene. The term “protein product of the gene” refersto proteins translated from RNA products of the gene. A number ofmethods can be used to detect or quantify the level of RNA products ofthe gene or genes within a sample, including microarrays, Real-Time PCR(RT-PCR; including quantitative RT-PCR), nuclease protection assays,RNA-sequencing (RNA-seq), and Northern blot analyses. In one embodiment,the assay uses the APPLIED BIOSYSTEMS™ HT7900 fast Real-Time PCR system.In addition, a person skilled in the art will appreciate that a numberof methods can be used to determine the amount of a protein product of agene of the methods disclosed herein, including immunoassays such asWestern blots, ELISA, and immunoprecipitation followed by SDS-PAGE andimmunocytochemistry. In certain embodiments, the expression level ofeach gene in the gene set is determined by reverse transcribing theisolated mRNA into cDNA and measuring a level of fluorescence for eachgene in the gene set by a nucleic acid sequence detection systemfollowing Real-Time Polymerase Chain Reaction (RT-PCR).

A person skilled in the art will appreciate that a number of detectionagents can be used to determine gene expression. For example, to detectRNA products of the biomarkers, probes, primers, complementarynucleotide sequences, or nucleotide sequences that hybridize to the RNAproducts can be used. In another example, to detect cDNA products of thebiomarkers, probes, primers, complementary nucleotide sequences, ornucleotide sequences that hybridize to the cDNA products can be used. Todetect protein products of the biomarkers, ligands or antibodies thatspecifically bind to the protein products can be used.

As used herein, the term “hybridize” refers to the sequence specificnon-covalent binding interaction with a complementary nucleic acid. Inone embodiment, the hybridization is under high stringency conditions.Appropriate stringency conditions that promote hybridization are knownto those skilled in the art.

As used herein, the terms “probe” and “primer” refer to a nucleic acidsequence that will hybridize to a nucleic acid target sequence. In oneexample, the probe and/or primer hybridizes to an RNA product of thegene or a complementary nucleic acid sequence. In another example, theprobe and/or primer hybridizes to a cDNA product. The length of probe orprimer depends on the hybridizing conditions and the sequences of theprobe or primer and nucleic acid target sequence. In one embodiment, theprobe or primer is at least 8, 10, 15, 20, 25, 50, 75, 100, 150, 200,250, 400, 500, or more than 500 nucleotides in length. Probes and/orprimers may include one or more label. Probes and/or primers may becommercially sourced from various providers (e.g., ThermoFisherScientific). In certain embodiments, a label may be any substancecapable of aiding a machine, detector, sensor, device, or enhanced orunenhanced human eye from differentiating a labeled composition from anunlabeled composition. Examples of labels include, but are not limitedto: a radioactive isotope or chelate thereof, dye (fluorescent ornon-fluorescent), stain, enzyme, or nonradioactive metal. Specificexamples include, but are not limited to: fluorescein, biotin,digoxigenin, alkaline phosphates, biotin, streptavidin, ³H, ¹⁴C, ³²P,³⁵S, or any other compound capable of emitting radiation, rhodamine,4-(4′-dimethylamino-phenylazo)benzoic acid;4-(4′-dimethylamino-phenylazo)sulfonic acid (sulfonyl chloride);5-((2-aminoethyl)-amino)-naphtalene-1-sulfonic acid; Psoralenederivatives, haptens, cyanines, acridines, fluorescent rhodolderivatives, cholesterol derivatives; ethylene-diamine-tetra-acetic acidand derivatives thereof, or any other compound that may bedifferentially detected. The label may also include one or morefluorescent dyes. Examples of dyes include, but are not limited to:CAL-Fluor Red 610, CAL-Fluor Orange 560, dR110, 5-FAM, 6FAM, dR6G, JOE,HEX, VIC, TET, dTAMRA, TAMRA, NED, dROX, PET, BHQ+, Gold540, and LIZ.

As used herein, a “sequence detection system” is any computationalmethod in the art that can be used to analyze the results of a PCRreaction. One example is the APPLIED BIOSYSTEMS™ HT7900 fast Real-TimePCR system. In certain embodiments, gene expression can be analyzedusing, e.g., direct DNA expression in microarray, Sanger sequencinganalysis, Northern blot, the NANOSTRING® technology, serial analysis ofgene expression (SAGE), RNA-seq, tissue microarray, or proteinexpression with immunohistochemistry or western blot technique. PCRgenerally involves the mixing of a nucleic acid sample, two or moreprimers that are designed to recognize the template DNA, a DNApolymerase, which may be a thermostable DNA polymerase such as Taq orPfu, and deoxyribose nucleoside triphosphates (dNTP's). Reversetranscription PCR, quantitative reverse transcription PCR, andquantitative real time reverse transcription PCR are other specificexamples of PCR. In real-time PCR analysis, additional reagents,methods, optical detection systems, and devices known in the art areused that allow a measurement of the magnitude of fluorescence inproportion to concentration of amplified DNA. In such analyses,incorporation of fluorescent dye into the amplified strands may bedetected or measured. In one embodiment, the expression level of eachgene in the gene set is determined by reverse transcribing the isolatedmRNA into cDNA and measuring a level of fluorescence for each gene inthe gene set by a nucleic acid sequence detection system followingReal-Time Polymerase Chain Reaction (RT-PCR).

As used herein, the terms “differentially expressed” or “differentialexpression” refer to a difference in the level of expression of thegenes that can be assayed by measuring the level of expression of theproducts of the genes, such as the difference in level of messenger RNAtranscript expressed (or converted cDNA) or proteins expressed of thegenes. In one embodiment, the difference can be statisticallysignificant. The term “difference in the level of expression” refers toan increase or decrease in the measurable expression level of a givengene as measured by the amount of messenger RNA transcript (or convertedcDNA) and/or the amount of protein in a sample as compared with themeasurable expression level of a given gene in a control, or controlgene or genes in the same sample (for example, a non-recurrence sample).In another embodiment, the differential expression can be compared usingthe ratio of the level of expression of a given gene or genes ascompared with the expression level of the given gene or genes of acontrol, wherein the ratio is not equal to 1.0. For example, an RNA,cDNA, or protein is differentially expressed if the ratio of the levelof expression in a first sample as compared with a second sample isgreater than or less than 1.0. For example, a ratio of greater than 1,1.2, 1.5, 1.7, 2, 3, 3, 5, 10, 15, 20, or more than 20, or a ratio lessthan 1, 0.8, 0.6, 0.4, 0.2, 0.1, 0.05, 0.001, or less than 0.0001. Inyet another embodiment, the differential expression is measured usingp-value. For instance, when using p-value, a biomarker is identified asbeing differentially expressed as between a first sample and a secondsample when the p-value is less than 0.1, less than 0.05, less than0.01, less than 0.005, or less than 0.001.

The terms “increased expression” or “decreased expression,” as usedherein, refer to an expression level of one or more genes, or prognosticRNA transcripts, or their corresponding cDNAs, or their expressionproducts that has been found to be differentially expressed in recurrentversus non-recurrent cSCC tumors. The higher the expression level of agene that predominantly has increased expression in tumors of patientswho had recurrence, the higher is the likelihood that the patientsuffering from this tumor is expected to have a poor clinical outcome(i.e., higher risk of recurrence, metastasis, or both). In contrast, thelower the expression level of a gene that predominantly has increasedexpressed in tumors of patients who have recurrent tumors, the higher isthe likelihood that the patient suffering from this tumor is expected tohave a promising clinical outcome (i.e., decreased risk of recurrence,metastasis, or both). The lower the expression level of a gene thatpredominantly has decreased expression in tumors of patients who hadrecurrence, the higher is the likelihood that the patient suffering fromthis tumor is expected to have a poor clinical outcome (i.e., higherrisk of recurrence, metastasis, or both). In contrast, the higher theexpression level of a gene that predominantly has decreased expressed intumors of patients who have recurrent tumors, the higher is thelikelihood that the patient suffering from this tumor is expected tohave a promising clinical outcome (i.e., decreased risk of recurrence,metastasis, or both).

References herein to the “same” level of biomarker indicate that thelevel of biomarker measured in each sample is identical (i.e., whencompared to the selected reference). References herein to a “similar”level of biomarker indicate that levels are not identical but thedifference between them is not statistically significant (i.e., thelevels have comparable quantities).

As used herein, the terms “control” and “standard” refer to a specificvalue that one can use to determine the value obtained from the sample.In one embodiment, a dataset may be obtained from samples from a groupof subjects known to have a cutaneous squamous cell carcinoma orsubtype. The expression data of the genes in the dataset can be used tocreate a control (standard) value that is used in testing samples fromnew subjects. In such an embodiment, the “control” or “standard” is apredetermined value for each gene or set of genes obtained from subjectswith a cutaneous squamous cell carcinoma whose gene expression valuesand tumor types are known. In certain embodiments of the methodsdisclosed herein, non-limiting examples of control genes can include,but are not limited to, BAG6 (probe ID: Hs00190383), KMT2D/MLL2 (probeID: Hs00912419_m1), MDM2 (probe ID: Hs00540450_s1), FXR1 (probe ID:Hs01096876_g1), KMT2C (probe ID: Hs01005521_m1), MDM4 (probe ID:Hs00967238_m1), VIM, and NF1B. In certain embodiments of the methodsdisclosed herein, the control genes are BAG6 (probe ID: Hs00190383),KMT2D/MLL2 (probe ID: Hs00912419_m1), MDM2 (probe ID: Hs00540450_s1),FXR1 (probe ID: Hs01096876_g1), KMT2C (probe ID: Hs01005521_m1), andMDM4 (probe ID: Hs00967238_m1). In some embodiments, a controlpopulation may comprise healthy individuals, individuals with cancer, ora mixed population of individuals with or without cancer. In certainembodiments, a control population may comprise individuals withnon-metastatic cancer or cancer that did not recur.

As used herein, the term “normal” when used with respect to a samplepopulation refers to an individual or group of individuals that does/donot have a particular disease or condition (e.g., cSCC or recurrentcSCC) and is also not suspected of having or being at risk fordeveloping the disease or condition. The term “normal” is also usedherein to qualify a biological specimen or sample (e.g., a biologicalfluid) isolated from a normal or healthy individual or subject (or groupof such subjects), for example, a “normal control sample.” The “normal”level of expression of a marker is the level of expression of the markerin cells in a similar environment or response situation, in a patientnot afflicted with cancer. A normal level of expression of a marker mayalso refer to the level of expression of a “reference sample” (e.g., asample from a healthy subject not having the marker associated disease).A reference sample expression may be comprised of an expression level ofone or more markers from a reference database. Alternatively, a “normal”level of expression of a marker is the level of expression of the markerin non-tumor cells in a similar environment or response situation fromthe same patient that the tumor is derived from.

As used herein, the terms “gene-expression profile,” “GEP,” or“gene-expression profile signature” refer to any combination of genes,the measured messenger RNA transcript expression levels, cDNA levels, ordirect DNA/RNA expression levels, or immunohistochemistry levels ofwhich can be used to distinguish between two biologically differentcorporal tissues and/or cells and/or cellular changes. In certainembodiments, a gene-expression profile is comprised of thegene-expression levels of 34 discriminant genes of ACSBG1, ALOX12,APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2,LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4,NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1,TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839. In some embodiments, the geneset further comprises 6 control genes or normalization genes selectedfrom: BAG6 (probe ID: Hs00190383), KMT2D/MLL2 (probe ID: Hs00912419_m1),MDM2 (probe ID: Hs00540450_s1), FXR1 (probe ID: Hs01096876_g1), KMT2C(probe ID: Hs01005521_m1), MDM4 (probe ID: Hs00967238_m1), VIM, andNF1B. In certain embodiments of the methods disclosed herein, the 6control genes are BAG6 (probe ID: Hs00190383), KMT2D/MLL2 (probe ID:Hs00912419_m1), MDM2 (probe ID: Hs00540450_s1), FXR1 (probe ID:Hs01096876_g1), KMT2C (probe ID: Hs01005521_m1), and MDM4 (probe ID:Hs00967238_m1).

In certain embodiments, a gene-expression profile is comprised of thegene-expression levels of at least 140, 139, 138, 137, 136, 135, 134,133, 132, 131, 130, 129, 128, 127, 126, 125, 124, 123, 122, 121, 120,119, 118, 117, 116, 115, 114, 113, 112, 111, 110, 109, 108, 107, 106,105, 104, 103, 102, 101, 100, 99, 98, 97, 96, 95, 94, 93, 92, 91, 90,89, 88, 87, 86, 85, 84, 83, 82, 81, 80, 79, 78, 77, 76, 75, 74, 73, 72,71, 70, 69, 68, 67, 66, 65, 64, 63, 62, 61, 60, 59, 58, 57, 56, 55, 54,53, 52, 51, 50, 49, 48, 47, 46, 45, 44, 43, 42, 41, 40, 39, 38, 37, 36,35, 34, 33, 32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18,17, 16, 15, 14, 13, 12, 11, or 10 genes, or less than 10 genes. In oneembodiment, the gene-expression profile is comprised of 56 genes. Inanother embodiment, the gene-expression profile is comprised of 40genes. In another embodiment, the gene-expression profile is comprisedof 30 genes. In another embodiment, the gene-expression profile iscomprised of 20 genes. In certain embodiments, the genes selected are:ACSBG1, AIM2, ALOX12, ANXA9, APOBEC3G, ARPC2, ATP6AP1, ATP6V0E2, BBC,BHLHB9, BLOC1S1, C1QL4, C21orf59, C3orf70, CCL27, CD163, CEP76, CHI3L1,CHMP2B, CXCL10, CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1,DUXAP8, EGFR, EphB2, FCHSD1, FDFT1, FLG, FN1, GTPBP2, HDDC3, HNRNPL,HOXA10 (HOXA9, MIR196B), HPGD, ID2, IL24, IL2RB, IL7R, INHBA, IPO5P1,KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LCE2B, LIME1 (ZGPAT),LOC100287896, LOC101927502, LOR, LRRC47, MIER2, MIR129-1, MIR3916,MKLN1, MMP1, MMP10, MMP12, MMP13, MMP3, MMP7, MMP9, MRC1, MRPL21,MSANTD4, MYC, NEB, NEFL, NFASC, NFIA, NFIB, NFIC, NOA1, PD1, PDL1, PDPN,PI3, PIG3, PIGBOS1, PIM2, PLAU, PLS3, PTHLH, PTRHD1, RBM33, RCHY1,RNF135, RPL26L1, RPP38, RUNX3, S100A8, S100A9, SEPT3, SERPINB2,SERPINB4, SLC1A3, SLC25A11, SNORD124, SPATA41, SPP1, TAF6L, TFAP2B,THYN1, TMEM41B, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM,YKT6, ZNF48, ZNF496, ZNF839, and/or ZSCAN31. In other embodiments, thegene set comprises 20 genes, 30 genes, or 40 genes selected from thegenes listed above. In some embodiments, the gene set further comprisescontrol genes or normalization genes selected from: BAG6 (probe ID:Hs00190383), KMT2D/MLL2 (probe ID: Hs00912419_m1), MDM2 (probe ID:Hs00540450_s1), FXR1 (probe ID: Hs01096876_g1), KMT2C (probe ID:Hs01005521_m1), MDM4 (probe ID: Hs00967238_m1), VIM, and NF1B.

As used herein, the term “predictive training set” refers to a cohort ofcSCC tumors with known clinical outcome for metastasis (i.e., localrecurrence, regional metastasis, distant metastasis, or any combination)and known genetic expression profile, used to define or establish allother cSCC tumors, based upon the genetic expression profile of each, asa low-risk, Class 1 tumor type or a high-risk, Class 2 tumor type.Additionally, included in the predictive training set is the definitionof “threshold points,” which are points at which a classification ofmetastatic risk is determined, specific to each individual geneexpression level.

As used herein, the term “altered in a predictive manner” refers tochanges in genetic expression profile that predict metastasis (i.e.,local recurrence, regional metastasis, distant metastasis, or anycombination), or predict overall survival. Predictive modeling riskassessment can be measured as: 1) a binary outcome having risk ofmetastasis or overall survival that is classified as low risk (e.g.,termed Class 1 herein) vs. high risk (e.g., termed Class 2 herein;wherein Class 2A is a high risk/moderate risk, and Class 2B is thehighest risk); and/or 2) a linear outcome based upon a probability scorefrom 0 to 1 that reflects the correlation of the genetic expressionprofile of a cSCC tumor with the genetic expression profile of thesamples that comprise the training set used to predict risk outcome.Within the probability score range from 0 to 1, a probability score, forexample, of less than 0.5 reflects a tumor sample with a low risk ofmetastasis (i.e., local recurrence, regional metastasis, distantmetastasis, or any combination), or death from disease, while aprobability score, for example, of greater than 0.5 reflects a tumorsample with a high risk of metastasis (i.e., local recurrence, regionalmetastasis, distant metastasis, or any combination), or death fromdisease. The increasing probability score from 0 to 1 reflectsincrementally declining metastasis free survival. In one embodiment, theprobability score is a bimodal, two-Class analysis, wherein a patienthaving a value of between 0 and 0.499 is designated as Class 1 (lowrisk; for example, having a 3-year relapse-free survival rate, a 3-yearmetastasis free survival rate, or a 3-year disease specific survivalrate of greater than 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%,or more than 95%) and a patient having a value of between 0.500 and 1.00is designated as Class 2 (high risk; for example, having a 3-yearmetastasis free survival rate, or a 3-year disease specific survivalrate of less than 50%, 45%, 40%, 35%, 30%, 25%, 20%, 15%, 10%, 5%, orless than 5%).

In certain embodiments, the probability score is a tri-modal,three-Class analysis, wherein patients are designated as Class 1 (lowrisk; for example having a recurrence risk of less than 25%, 20%, 15%,10%, 5%, or less than 5%), Class 2A (moderate risk; for example having arecurrence risk of 75%, 70%, 65%, 60%, 55%, 50%, 45%, 40%, 35%, 30%,25%, or any number in between), or Class 2B (high risk; for example,having a recurrence risk of 75%, 80%, 85%, 90%, 95%, or higher than95%). To develop a ternary, or three-Class system of risk assessment,with Class 1 having a low risk of metastasis (i.e., local recurrence,regional metastasis, distant metastasis, or any combination) or deathfrom disease, Class 2A having an moderate risk, and Class 2B having ahigh risk, the median probability score value for all low risk or highrisk tumor samples in the training set was determined, and one standarddeviation from the median was established as a numerical boundary todefine low or high risk. For example, low risk cSCC tumors within theternary classification system can have a 3-year metastasis free survivalof 100% (e.g., Class 1; with a probability score of 0-0.337), comparedto high risk (e.g., Class 2B; with a probability score of 0.673-1) cSCCtumors which can have a 20% 3-year metastasis free survival. Casesfalling outside of one standard deviation from the median low or highrisk probability scores have an moderate risk, and moderate risk (Class2A; with a probability score of 0.338-0.672) cSCC tumors can have a 55%3-year metastasis free survival rate.

The TNM (Tumor-Node-Metastasis) status system is the most widely usedcancer staging system among clinicians and is maintained by the AmericanJoint Committee on Cancer (AJCC) and the International Union for CancerControl (UICC). Cancer staging systems codify the extent of cancer toprovide clinicians and patients with the means to quantify prognosis forindividual patients and to compare groups of patients in clinical trialsand who receive standard care around the world.

Local recurrence rates for cSCC have been reported to be 1-10%, but canbe as high as 47% in patients who have cSCCs with high-risk clinicalfeatures. While the overall rate of metastasis is ˜5%, this rateincreases up to ˜45% in patients with high-risk clinical features or whohave already experienced a recurrence. After regional or distantmetastasis occurs, prognosis is usually poor, with 5-year survival ratesranging from 26-34% and 10-year survival rates of 16%. Although theoverall percentages of patients who die from cSCC (˜1%) are low, theabsolute number of deaths are estimated to be equal to or greater thanthose attributed to melanoma, due to the large number of yearly cSCCdiagnoses (400,000-700,000 patients), and account for the majority ofNMSC-related deaths. In effect, local and regional recurrence fromprimary cSCC tumors remains a significant health burden.

Cutaneous squamous cell carcinoma stems from interfollicular epidermalkeratinocytes and can arise from precancerous lesions, the most commonof which are actinic keratoses. Once the malignant cells enter thedermis, the cSCC becomes invasive. Squamous cell carcinoma can presentas smooth or hyperkeratinized lesions that are pink or skin-colored.They can exhibit ulceration and bleed when traumatized. Risk factorsthat contribute to the development of cSCC include exposures toultraviolet radiation, ionizing radiation, and chemicals, as well asincreased age and male gender. Immunosuppressed individuals, those witha history of non-Hodgkin lymphoma, including chronic lymphocyticleukemia, those with certain genetic skin conditions, and those who havehad organ transplants are at a significantly increased risk fordeveloping cSCC. In fact, the latter group has risk up to 100 times thatof the normal population. Some drugs used to treat other types of skincancer (e.g., basal cell carcinoma (BCC), melanoma), including hedgehog,BRAF, and MET inhibitors, can also increase the propensity for cSCC.Small, low-risk lesions can be treated with cryosurgery, curettage andelectrodessication, or surgery, while larger, higher risk lesions aregenerally treated with surgical excision or Mohs surgery. Radiotherapycan be used in conjunction with surgery if margins are not clearedsurgically or if there is perineural invasion. If regional recurrenceoccurs, the lymph nodes are the primary site of involvement, accountingfor ˜80-85% of cSCC recurrences, while distant metastasis occurs in˜15-20% of patients.

Because the development of regional or distant metastasis leads to anincrease death from cSCC and because there are effective adjuvantinterventions, there has been an increased interest in more accuratelyidentifying such lesions beyond clinical and pathologic features alone.As such, the National Comprehensive Cancer Network (NCCN) and AmericanJoint Committee on Cancer (AJCC) have recently proposed parameters todistinguish high risk lesions and follow-up measures for these lesions.These high-risk features include tumor size and location (“mask” areasof the face and/or ear and non-glabrous lip), increased thickness orClark's level, immunosuppression, recurrent lesions, sites of chronicinflammation or previous radiation, poor differentiation, and perineuralinvasion. However, high-risk cSCC definitions from different groups arediscordant, with the AJCC classifying a majority of lesions as low-riskand NCCN classifying a majority as high-risk. Such discrepancies,especially in the T2a and T2b groups, have led to the proposal ofalternative staging criteria that can better elucidate high risk cSCCcases. However, in an attempt to improve the positive predictive values,these alternative approaches have a lower sensitivity and categorizemany patients who will metastasize as low risk. In effect, there is aclinically unmet need for better markers to identify high-risk lesions,particularly molecular biomarkers that can be objectively evaluated. Thevalidated prognostic gene expression profiles disclosed herein couldinform clinical decision-making on, for example: (1) preoperativesurgical staging, based on shave biopsy; (2) adjuvant radiation, nodalstaging, adjuvant systemic therapy to reduce regional/distantmetastasis; and (3) improving identification of patients with cSCC whocan benefit from surgical, radiation and immunotherapy interventions.

Squamous cell carcinoma that is predicted to have an increased risk ofrecurrence, progression, or metastasis can be treated with an aggressivecancer treatment regimen (see NCCN Guidelines® v1. 2020—October 2019).Advanced cSCC may be defined under two headings: (1) local disease;and/or (2) regional nodal/distant metastases. Local disease can bedifficult to control and/or treat if: (1) the primary cSCC has invadedinto neuronal or vascular structures; (2) there is presence of lymphnode metastases, which indicate advanced disease; or (3) distantmetastases have been detected.

In an embodiment, a method for predicting risk of metastasis (i.e.,recurrence, regional metastasis, distant metastasis, or anycombination), in a patient with a cutaneous squamous cell carcinoma(cSCC) tumor is disclosed herein, the method comprising: (a) obtaining acSCC tumor sample from the patient and isolating mRNA from the sample;(b) determining the expression level of 34 genes in a gene set; whereinthe 34 genes in the gene set are selected from: ACSBG1, ALOX12,APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2,LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4,NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1,TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839; (c) comparing the expressionlevels of the 34 genes in the gene set from the cSCC tumor sample to theexpression levels of the 34 genes in the gene set from a predictivetraining set to generate a probability score of the risk of metastasis(local recurrence, regional metastasis, distant metastasis, or anycombination); and (d) providing an indication as to whether the cSCCtumor has a low risk to a high risk of local metastasis (recurrence,regional metastasis, distant metastasis, or any combination), based onthe probability score generated in step (c).

In some embodiments, the expression level of each gene in the gene setis determined by reverse transcribing the isolated mRNA into cDNA andmeasuring a level of fluorescence for each gene in the gene set by anucleic acid sequence detection system following Real-Time PolymeraseChain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sampleis obtained from formalin-fixed, paraffin embedded sample. In oneembodiment, the method further comprises identifying the cSCC tumor ashaving a high risk of metastasis (i.e., local recurrence, regionalmetastasis, distant metastasis, or any combination), based on theprobability score, and administering to the patient an aggressive tumortreatment.

In another embodiment, the gene set comprises at least one additionalgene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1,C1QL4, C21orf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10, CXCR4,CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1, EGFR, EphB2, FCHSD1,FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24, IL2RB,IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR,LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13, MMP3, MMP7,MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3,PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9,SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM41B,TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/orZSCAN31. In other embodiments, the gene set comprises an additional 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40genes selected from the genes listed above.

In an embodiment, a method for predicting risk of metastasis (i.e.,recurrence, metastasis, or both), in a patient with a cutaneous squamouscell carcinoma (cSCC) tumor is disclosed herein, the method comprising:(a) obtaining a cSCC tumor sample from the patient and isolating mRNAfrom the sample; (b) determining the expression level of 34 genes in agene set; wherein the 34 genes in the gene set are selected from:ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2,HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10,MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38,RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839; and (c)providing an indication as to whether the cSCC tumor has a low risk to ahigh risk of metastasis (i.e., local recurrence, regional metastasis,distant metastasis, or any combination), based on the expression levelof 34 genes generated in step (b).

In some embodiments, the expression level of each gene in the gene setis determined by reverse transcribing the isolated mRNA into cDNA andmeasuring a level of fluorescence for each gene in the gene set by anucleic acid sequence detection system following Real-Time PolymeraseChain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sampleis obtained from formalin-fixed, paraffin embedded sample.

In another embodiment, the gene set comprises at least one additionalgene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1,C1QL4, C21orf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10, CXCR4,CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1, EGFR, EphB2, FCHSD1,FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24, IL2RB,IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR,LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13, MMP3, MMP7,MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3,PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9,SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM41B,TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/orZSCAN31. In other embodiments, the gene set comprises an additional 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40genes selected from the genes listed above.

In certain embodiments, the expression level of: ACSBG1 is decreased,AIM2 is increased, ALOX12 is decreased, ANXA9 is decreased, APOBEC3G isincreased, ARPC2 is decreased, ATP6AP1 is decreased, ATP6V0E2 isincreased, BBC is increased, BHLHB9 is decreased, BLOC1S1 is decreased,C1QL4 is increased, C21orf59 is increased, C3orf70 is increased, CCL27is decreased, CD163 is increased, CEP76 is decreased, CHI3L1 isincreased, CHMP2B is decreased, CXCL10 is decreased, CXCR4 is increased,CYP2D6 (LOC101929829) is decreased, DARS is decreased, DCT is decreased,DDAH1 is decreased, DSS1 is decreased, DUXAP8 is increased, EGFR isincreased, EphB2 is increased, FCHSD1 is decreased, FDFT1 is decreased,FLG is decreased, FN1 is increased, GTPBP2 is decreased, HDDC3 isincreased, HNRNPL is decreased, HOXA10 (HOXA9, MIR196B) is decreased,HPGD is decreased, ID2 is decreased, IL24 is increased, IL2RB isdecreased, IL7R is increased, INHBA is increased, IPO5P1 is increased,KIT is increased, KLK5 is decreased, KRT17 is decreased, KRT18 isincreased, KRT19 is decreased, KRT6B is decreased, LAMC2 is decreased,LCE2B is decreased, LIME1 (ZGPAT) is increased, LOC100287896 isincreased, LOC101927502 is decreased, LOR is decreased, LRRC47 isincreased, MIER2 is increased, MIR129-1 is increased, MIR3916 isincreased, MKLN1 is increased, MMP1 is increased, MMP10 is decreased,MMP12 is increased, MMP13 is increased, MMP3 is increased, MMP7 isincreased, MMP9 is decreased, MRC1 is increased, MRPL21 is increased,MSANTD4 is decreased, MYC is decreased, NEB is decreased, NEFL isdecreased, NFASC is decreased, NFIA is decreased, NFIB is decreased,NFIC is decreased, NOA1 is increased, PD1 is decreased, PDL1 isincreased, PDPN is increased, PI3 is decreased, PIG3 is decreased,PIGBOS1 is increased, PIM2 is increased, PLAU is increased, PLS3 isdecreased, PTHLH is decreased, PTRHD1 is decreased, RBM33 is increased,RCHY1 is increased, RNF135 is increased, RPL26L1 is increased, RPP38 isdecreased, RUNX3 is increased, S100A8 is decreased, S100A9 is decreased,SEPT3 is decreased, SERPINB2 is decreased, SERPINB4 is decreased, SLC1A3is increased, SLC25A11 is increased, SNORD124 is increased, SPATA41 isincreased, SPP1 is increased, TAF6L is increased, TFAP2B is decreased,THYN1 is increased, TMEM41B is decreased, TNNC1 is decreased, TUBB3 isdecreased, TUFM (MIR4721) is increased, TYRP1 is decreased, UGP2 isdecreased, USP7 is decreased, VIM is increased, YKT6 is increased, ZNF48is increased, ZNF496 is increased, ZNF839 is increased, and/or ZSCAN31is decreased. In certain embodiments, the increase or decrease in theexpression level is the gene level from a recurrent tumor sample versusa non-recurrent tumor sample.

In an embodiment, a method for treating a patient with cutaneoussquamous cell carcinoma (cSCC) tumor is disclosed herein, the methodcomprising: (a) obtaining a cSCC tumor sample from the patient andisolating mRNA from the sample; (b) determining the expression level of34 genes in a gene set; wherein the 34 genes in the gene set areselected from: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76,DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896,LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1,RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, andZNF839; (c) providing an indication as to whether the cSCC tumor has alow risk to a high risk of local metastasis (i.e., recurrence, regionalmetastasis, distant metastasis, or any combination), based on theexpression level of 34 genes generated in step (b); and (d)administering to the patient an aggressive treatment when thedetermination is made in the affirmative that the patient has a cSCCtumor with a high risk of metastasis (i.e., local recurrence, regionalmetastasis, distant metastasis, or any combination).

In some embodiments, the expression level of each gene in the gene setis determined by reverse transcribing the isolated mRNA into cDNA andmeasuring a level of fluorescence for each gene in the gene set by anucleic acid sequence detection system following Real-Time PolymeraseChain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sampleis obtained from formalin-fixed, paraffin embedded sample.

In another embodiment, the gene set comprises at least one additionalgene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1,C1QL4, C21orf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10, CXCR4,CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1, EGFR, EphB2, FCHSD1,FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24, IL2RB,IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR,LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13, MMP3, MMP7,MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3,PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9,SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM41B,TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/orZSCAN31. In other embodiments, the gene set comprises an additional 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40genes selected from the genes listed above.

As used herein, the terms “treatment,” “treat,” or “treating” refer to amethod of reducing the effects of a disease or condition or symptom ofthe disease or condition. Thus, in the methods disclosed herein,treatment can refer to a 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%,90%, or 100% reduction in the severity of an established disease orcondition or symptom of the disease or condition. For example, a methodof treating a disease is considered to be a treatment if there is a 5%reduction in one or more symptoms of the disease in a subject ascompared to a control. Thus, the reduction can be a 5%, 10%, 20%, 30%,40%, 50%, 60%, 70%, 80%, 90%, 100% or any percent reduction between 5%and 100% as compared to native or control levels. It is understood thattreatment does not necessarily refer to a cure or complete ablation ofthe disease, condition, or symptoms of the disease or condition. After acSCC is found and staged, a medical professional or team of medicalprofessionals will recommend one or several treatment options. Indetermining a treatment plan, factors to consider include the type,location, and stage of the cancer, as well as the patient's overallphysical health. Patients with cSCC typically are managed by a healthcare team made up of doctors from different specialties, such as: adermatologist (in particular, a dermatologist who specializes in Mohsmicrographic surgery), an orthopedic surgeon (in particular, a surgeonwho specializes in diseases of the bones, muscles, and joints), asurgical oncologist, a thoracic surgeon, a medical oncologist, aradiation oncologist, and/or a physiatrist (or rehabilitation doctor).After a cSCC is found and staged, a medical professional or team ofmedical professionals will typically recommend one or several treatmentoptions including one or more of surgery, radiation, chemotherapy, andtargeted therapy.

The NCCN Guidelines® define low risk cSCC tumors as tumors that involve:(1) an area of less than 20 mm (for truck and extremities) or less than10 mm for the cheeks, forehead, scalp, neck and pretibial; (2) welldefined borders; (3) primary cSCC tumor; (4) not rapidly growing; (5)from a patient who has no neurologic symptoms and is not consideredimmunosuppressed; (6) from a site free of chronic inflammation; (7) wellor moderately differentiated; (8) free of acantholytic, adenosquamous,desmoplastic, or metaplastic subtypes; (9) depths of less than 2 mm; and(10) free of perineural, lymphatic, or vascular involvement.

The NCCN Guidelines® define high risk cSCC tumors as tumors thatinvolve: (1) an area of greater than 20 mm (for trunk and extremities),greater than 10 mm for the cheeks, forehead, scalp, neck and pretibial,or any cSCC involving the “mask areas” (such as central face, eyelids,eyebrows, periorbital, nose, lips, chin, mandible, temple or ear),genitalia, hands and feet; (2) poorly defined borders; (3) recurrentcSCC tumor; (4) rapidly growing; (5) from a patient who has neurologicsymptoms or is considered immunosuppressed; (6) from a site with chronicinflammation; (7) poorly differentiated; (8) presence of acantholytic,adenosquamous, desmoplastic, or metaplastic subtypes; (9) depths ofgreater than or equal 2 mm; and (10) presence of perineural, lymphatic,or vascular involvement.

As used herein, the term “aggressive cancer treatment regimen” refers toa treatment regimen that is determined by a medical professional or teamof medical professionals and can be specific to each patient. In certainembodiments, a cSCC tumor predicted to have a high-risk of recurrence ora high-risk of metastasis, or a decreased chance of survival using themethods and kits disclosed herein, would be treated using an aggressivecancer treatment regimen. Whether a treatment is considered to beaggressive will generally depend on the cancer-type, the age of thepatient, and other factors known to those of skill in the art. Forexample, in breast cancer, adjuvant chemotherapy is a common aggressivetreatment given to complement the less aggressive standards of surgeryand hormonal therapy. Those skilled in the art are familiar with variousother aggressive and less aggressive treatments for each type of cancer.An aggressive cancer treatment regimen is defined by the NationalComprehensive Cancer Network (NCCN), and has been defined in the NCCNGuidelines® as including one or more of: 1) imaging (CT scan, PET/CT,MRI, chest X-ray), 2) discussion and/or offering of tumor resection if atumor is determined to be resectable (e.g., by Mohs micrographic surgeryor resection with complete circumferential margin assessment), 3)radiation therapy (RT), 4) chemoradiation, 5) chemotherapy, 6) regionallimb therapy, 7) palliative surgery, 8) systemic therapy, 9)immunotherapy, and 10) inclusion in ongoing clinical trials. Guidelinesfor clinical practice are published in the National Comprehensive CancerNetwork (NCCN Guidelines® Squamous Cell Skin Cancer Version 2.2018,updated Oct. 5, 2017, available on the World Wide Web at NCCN.org).

Additional therapeutic options may include, but are not limited to: 1)combination regimens such as: AD (doxorubicin, dacarbazine); AIM(doxorubicin, ifosfamide, mesna); MAID (mesna, doxorubicin, ifosfamide,dacarbazine); ifosfamide, epirubicin, mesna; gemcitabine and docetaxel;gemcitabine and vinorelbine; gemcitabine and dacarbazine; doxorubicinand olaratumab; methotrexate and vinblastine; tamoxifen and sulindac;vincristine, dactinomycin, cylclophosphamide; vincristine, doxorubicin,cyclophosphamide; vincristine, doxorubicin, cyclophosphamide withifosfamide and etoposide; vincristine, doxorubicin, ifosfamide;cyclophosphamide topotecan; or ifosfamide, doxorubicin; and/or 2) singleagents, such as: cisplatin or other metallic compounds,5-FU/capecitabine (Xeloda®), cetuximab (Erbitux®), cemiplimab(Libtayo®), pembrolizumab (MK-3475), panitumumab (Vectibix®),dacomitinib (PF-00299804), gefitinib (ZD1839, Iressa), doxorubicin,ifosfamide, epirubicin, gemcitabine, dacarbazine, temozolomide,vinorelbine, eribulin, trabectedin, pazopanib, imatinib, sunitinib,regorafenib, sorafenib, nilotinib, dasatinib, interferon, toremifene,methotrexate, irinotecan, topotecan, paclitaxel, nab-paclitaxel(abraxane), docetaxel, bevacizumab, temozolomide, sirolimus (Rapamune®),everolimus, temsirolimus, crizotinib, ceritinib, or palbociclib.

While surgical excision remains the mainstay for treating operable(Stage I-III) cSCC patients, for Stage I patients, en bloc resectionwith negative margins is generally considered sufficient for long-termlocal control. For those with incomplete excision margins and/or otherunfavorable pathologic features, pre- or post-operative chemotherapyand/or radiation treatment can be recommended. No therapy has shownconsistent efficacy for the treatment of excised cSCC, and treatmentoptions for unresectable or advanced cSCC are limited.

Immunotherapy using an anti-PD1 inhibitor has shown promising results inearly phase studies with cSCC patients. Examples of immunotherapies(that can be used alone or in combination with any one or more of tumorresection if a tumor is determined to be resectable, radiation therapy,chemoradiation, chemotherapy, regional limb therapy, palliative surgery,systemic therapy, additional immunotherapeutic, or inclusion in ongoingclinical trials), can include, for example, pembrolizumab (Keytruda®)and nivolumab (Opdivo®), cemiplimab (Libtayo®; a fully human monoclonalantibody to Programmed Death-1). PD-1 is a protein on T-cells thatnormally help keep T-cells from attacking other cells in the body. Byblocking PD-1, these drugs can boost the immune response against cancercells. CTLA-4 inhibitors (for example, ipilimumab (Yervoy®)) are anotherclass of drugs that can boost the immune response. In some instances,cytokine therapy (such as, interferon-alpha and interleukin-2) can beused to boost the immune system. Examples of interferon andinterleukin-based treatments can include, but are not limited to,aldesleukin (Proleukin®), interferon alpha-2b (INTRON®), and pegylatedinterferon alpha-2b (Sylvatron®; PEG-INTRON®, PEGASYS). In anotherembodiment, oncolytic virus therapy can be used. Along with killing thecells directly, the oncolytic viruses can also alert the immune systemto attack the cancer cells. For example, talimogene laherparepvec(Imlygic®), also known as T-VEC, is an oncolytic virus that can be usedto treat melanomas. Additional immunotherapies may include CV8102.

Additionally, targeted therapies may be used to treat patients withcSCC. For example, targeted therapies can include, but are not limitedto, vemurafenib (Zelboraf®), dabrafenib (Tafinlar®), trametinib(Mekinist®), CLL442, and cobimetinib (Cotellic®). These drugs targetcommon genetic mutations, such as the BRAFV600 mutation, that may befound in a subset of cSCC patients.

In certain embodiments, the methods as disclosed herein can be used todetermine a recommended risk-aligned management plan. For example,patients determined to have a low risk (Class 1) tumor can be managedunder a low intensity management plan. A low intensity management plancan comprise minimal clinical follow-up (e.g., 1-2× per year), a reducedimaging (low frequency or no imaging performed), a reduced nodalassessment (palpation only), and/or an avoidance of adjuvant radiationor chemotherapy. For example, patients determined to have a moderaterisk (Class 2A) tumor can be managed under a moderate intensitymanagement plan. A moderate intensity management plan can comprise ahigh frequency of clinical follow-up (e.g., 2-4× per year for about 3years), imaging (e.g., baseline and annual nodal US/CT for 2 years),consideration of nodal biopsy or elective neck dissection, and/or aconsideration of adjuvant radiation or chemotherapy. For example,patients determined to have a high risk (Class 2B) tumor can be managedunder a high intensity management plan. A high intensity management plancan comprise the highest frequency of clinical follow-up (e.g., 4-12×per year for about 3 years), imaging (e.g., baseline and 4× per yearnodal US/CT for 2 years), recommendation of nodal biopsy or electiveneck dissection, and/or a recommendation of adjuvant radiation,chemotherapy, and/or clinical trials. Importantly, these risk-stratifiedmanagement plans fall within the current NCCN Guidelines® for patientsidentified as having a high risk cSCC tumor as defined by clinical andpathologic features only (see also FIG. 15).

As used herein, the term “adjuvant therapy” refers to additional cancertreatment given after a primary treatment to lower the risk that thecancer will recur. For example, adjuvant therapy is often used beforeand/or after a primary surgical treatment in order to decrease thechance of the primary cancer recurring. In surgery, where all detectabledisease has been removed, there remains a statistical risk of relapse orrecurrence due to the presence of undetected disease. Adjuvant therapygiven before the primary treatment is called neoadjuvant therapy.Neoadjuvant therapy can also decrease the chance of the cancerrecurring, and it's often used to make the primary treatment, such as anoperation or radiation treatment more effective. Adjuvant therapy caninclude chemotherapy, radiation therapy, hormone therapy, targetedtherapy, immunotherapies, or biological therapy.

In some embodiments, the cSCC tumor is a frozen sample. In anotherembodiment, the cSCC sample is formalin-fixed and paraffin embedded. Incertain embodiments, the cSCC sample is taken from a formalin-fixed,paraffin embedded wide local excision sample. In another embodiment, thecSCC tumor is taken from a formalin-fixed, paraffin embedded primarybiopsy sample. In some embodiments, the cSCC sample can be from imageguided surgical biopsy, shave biopsy, wide excision, or a lymph nodedissection.

In certain embodiments, analysis of genetic expression and determinationof outcome is carried out using radial basis machine and/or partialleast squares analysis (PLS), partition tree analysis, logisticregression analysis (LRA), K-nearest neighbor, neural networks, ensemblelearners, voting algorithms, or other algorithmic approach. Theseanalysis techniques take into account the large number of samplesrequired to generate a training set that will enable accurate predictionof outcomes as a result of cut-points established with an in-processtraining set or cut-points defined for non-algorithmic analysis, butthat any number of linear and nonlinear approaches can produce astatistically significant and clinically significant result. As usedherein, the term “Kaplan-Meier survival analysis” is understood in theart to be also known as the product limit estimator, which is used toestimate the survival function from lifetime data. In medical research,it is often used to measure the fraction of patients living for acertain amount of time after treatment. JMP GENOMICS®, R, Pythonlibraries including SciPy, SciKit, and numpy software or systems such asTensorFlow provides an interface for utilizing each of the predictivemodeling methods disclosed herein, and should not limit the claims tomethods performed only with JMP GENOMICS®, R, Python, or TensorFlowsoftware.

In an embodiment, a kit comprising primer pairs suitable for thedetection and quantification of nucleic acid expression of 34 genes isdisclosed herein, wherein the 34 genes are selected from: ACSBG1,ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3,ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1,MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3,SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839.

In some embodiments, the primer pairs suitable for the detection andquantification of nucleic acid expression of 34 genes are primer pairsfor: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8,GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502,MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135,RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839. Inother embodiments, the primer pairs comprise primer pairs for at leastone additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1,BLOC1S1, C1QL4, C21orf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10,CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1, EGFR, EphB2,FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24,IL2RB, IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B,LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13,MMP3, MMP7, MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1,PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8,S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1,TMEM41B, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6,and/or ZSCAN31. In other embodiments, the gene set comprises anadditional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, ormore than 40 genes selected from the genes listed above.

In another aspect, this disclosure relates to kits to be used inassessing the expression of a gene or set of genes in a cSCC sample orbiological sample from a subject to assess the risk of developingrecurrence, metastasis, or both. In one embodiment, the disclosurerelates to a kit comprising primer pairs suitable for the detection andquantification of nucleic acid expression of 34 genes selected from:ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2,HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10,MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38,RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839.

Kits can include any combination of components that facilitates theperformance of an assay. A kit that facilitates assessing the expressionof the gene or genes may include suitable nucleic acid-based and/orimmunological reagents as well as suitable buffers, control reagents,and printed protocols. A “kit” is any article of manufacture (e.g., apackage or container) comprising at least one reagent, e.g., a probe orprimer set, for specifically detecting a marker or set of markers usedin the methods disclosed herein. The article of manufacture may bepromoted, distributed, sold, or offered for sale as a unit forperforming the methods disclosed herein. The reagents included in such akit comprise probes, primers, or antibodies for use in detecting one ormore of the genes and/or gene sets disclosed herein and demonstrated tobe useful for predicting recurrence, metastasis, or both, in patientswith cSCC. Kits that facilitate nucleic acid based methods may furtherinclude one or more of the following: specific nucleic acids such asoligonucleotides, labeling reagents, enzymes including PCR amplificationreagents such as Taq or Pfu, reverse transcriptase, or other, and/orreagents that facilitate hybridization. In addition, the kits disclosedherein may preferably contain instructions which describe a suitabledetection assay. Such kits can be conveniently used, e.g., in clinicalsettings, to diagnose and evaluate patients exhibiting symptoms ofcancer, in particular patients exhibiting the possible presence of acutaneous squamous cell carcinoma.

EXAMPLES

The Examples that follow are illustrative of specific embodiments of theclaimed invention, and various uses thereof. They are set forth forexplanatory purposes only, and should not be construed as limiting thescope of the claimed invention in any way.

Example 1: cSSC Tumor Sample Preparation and Expression Analysis

a. cSCC Tumor Sample Preparation and RNA Isolation

Formalin-fixed paraffin embedded (FFPE) primary squamous cell carcinomatumor specimens arranged in 5 μm sections on microscope slides wereacquired from multiple institutions under Institutional Review Board(IRB) approved protocols. All tissue was reviewed by a pathologist.Tissue was marked and tumor tissue was dissected from the slide using asterile disposable scalpel, collected into a microcentrifuge tube, anddeparaffinized using xylene. RNA was isolated from each specimen usingthe QIAGEN QIAsymphony RNA kit (Hilden, Germany) on the QIAGENQIAsymphony SP sample preparation automated extractor. RNA quantity wasassessed using the NanoDrop™ 8000 system.

b. cDNA Generation and RT-PCR Analysis

RNA isolated from FFPE samples was converted to cDNA using the AppliedBiosystems High Capacity cDNA Reverse Transcription Kit (LifeTechnologies Corporation, Grand Island, N.Y.). Prior to performing theRT-PCR assay, each cDNA sample underwent a 14-cycle pre-amplificationstep. Pre-amplified cDNA samples were diluted 20-fold in TE buffer. 7.5μL of each diluted sample was mixed with 7.5 μL of TaqMan OpenArrayReal-Time Mastermix, and the solution was loaded to a custom highthroughput microfluidics OpenArray card containing primers specific forthe genes. Each sample was run in triplicate. The gene expressionprofile test was performed on a ThermoFisher QuantStudio12k FlexReal-Time PCR system (Life Technologies Corporation, Grand Island,N.Y.).

c. Expression Analysis and Class Assignment

Mean C_(t) values were calculated for triplicate sample sets, and ΔC_(t)values were calculated by subtracting the mean C_(t) of eachdiscriminating gene from the geometric mean of the mean C_(t) values ofall endogenous control genes. ΔC_(t) values were standardized accordingto the mean of the expression of all discriminant genes with a scaleequivalent to the standard deviation. Various predictive modelingmethods, including radial basis machine, k-nearest neighbor, partitiontree, logistic regression, discriminant analysis and distance scoring,and neural network analysis were performed using R version 3.3.2.

Example 2: cSCC Metastatic Risk Genetic Signature and BiomarkerExpression

The study design workflow is shown in FIG. 1. First, in order to developthe gene expression profile for cSCC prognostication, cases withannotated clinical data and sufficient follow-up were used as adevelopment set. Pre-specified bins of patients within the recurrent andnon-recurrent group were created, including immunocompromised,immunocompetent, those with a certain number of high risk features andlow risk cases. The goal was to satisfy the pre-specified number ofcases in each bin for development. Predictive modeling was performed ongene expression data from the development cohort. The predictive modelwas then validated. 221 cases were included in the development set (seeTable 1). Table 1 shows the demographics for the cohort of 221 casesused in this study. They are also stratified by non-recurrence orrecurrence. Recurrence is defined as any recurrence—local nodal(satellitosis through regional nodes and distant metastasis). Note thatcases with R1 or R2 and local recurrence in the scar or contiguous tothe scar were embargoed from this analysis. Characteristics that areassociated with higher risk tumors (such as male sex, compromised immunesystem, head and neck primary tumor, poor differentiation orundifferentiated, higher Clark Level, perineural invasion, and invasioninto subcutaneous fat) are features included. This is after embargoingcases that have not yet had data monitoring and did not meet verystringent gene expression data requirements.

TABLE 1 Demographics for the cohort of 221 cases used in Examples 2 and3 Non- With All Recurrence Recurrence Feature (n = 221) (n = 196) (n =25) p-value Age: Median years (range) 74 (43-97) 74 (45-97) 69 (43-91)n.s. Mean +/− SD 72.8 +/− 11.2 73.3 +/− 10.8 68.6 +/− 13.2 Definitivesurgery: Mohs 181 (82%) 161 (82%) 20 (80%) n.s. WLE 39 (18%) 34 (17%) 5(20%) Male sex 164 (74%) 143 (73%) 21 (84%) n.s. Patientimmunocompromised 30 (14%) 20 (10%) 10 (40%) p < 0.001 Located on heador neck 146 (66%) 129 (66%) 17 (68%) n.s. Tumor diameter: Median cm(range) 1.4 (0-28) 1.15 (0-8.8) 2.9 (0.25-28) p < 0.001 Mean +/− SD 1.88+/− 2.34 1.62 +/− 1.47 3.89 +/− 5.27 Differentiation Status:Poor/Undifferentiated 12 (5%) 9 (5%) 3 (12%) p < 0.001 Clark Level IV/V73 (33%) 67 (34%) 6 (24%) p < 0.001 Perineural invasion present 12 (5%)9 (5%) 3 (12%) p < 0.001 Invasion into subcutaneous fat 22 (10%) 19(10%) 3 (12%) P = 0.015

Gene expression differences (RT-PCR data from 73 genes) betweenrecurrent and non-recurrent cSCC cases were evaluated. Using the geneexpression data, several control genes were identified that had stableexpression across all of the samples. These control genes were then usedto normalize the expression of the remaining genes. Gene expressiondifferences between recurrent and non-recurrent cases were investigatedto find the genes that are significant. Significant gene expressiondifferences that were associated with local recurrences, regionalmetastases, and distant metastases were also evaluated. Table 2 belowshows genes associated with regional/distant metastases. Geneticexpression of the discriminant genes in the signature (Table 2) wasassessed in a cohort of 240 cSCC samples using RT-PCR, 18 of these wereindependently significant to a p-value of p<0.05 (see FIG. 2). As shownin Table 3 below, of the 63 discriminating genes, 18 were altered inmetastatic cSCC tumors compared to nonmetastatic tumors with a p-valueof p<0.05.

TABLE 2 63 candidate genes for the GEP signature to predict metastaticrisk and/recurrence in cSCC tumors Gene symbol p-value mean - Recurrencemean - Non-Recurrence LOR 0.000 0.310 2.935 KRT18 0.000 0.454 −1.081LCE2B 0.000 0.447 2.490 EphB2 0.001 −1.846 −2.648 FLG 0.001 −4.104−1.594 DCT 0.001 −5.696 −3.003 TFAP2B 0.001 −6.571 −3.836 NEB 0.002−3.495 −2.807 TYRP1 0.006 −5.869 −3.709 MMP3 0.006 −2.887 −5.159 MMP70.010 −3.915 −5.568 MMP1 0.014 2.290 0.970 INHBA 0.016 −1.203 −2.222ACSBG1 0.024 −3.613 −2.489 USP7 0.029 0.689 1.076 APOBEC3G 0.035 −3.800−4.260 NFIB 0.036 −2.623 −2.385 ANXA9 0.050 −8.007 −7.059 RCHY1 0.055−2.418 −2.665 PDPN 0.056 1.672 1.251 ALOX12 0.066 −4.112 −3.688 YKT60.070 1.449 1.140 PLAU 0.091 1.873 1.913 ID2 0.110 −0.921 −0.550 MMP100.119 −0.067 −1.164 HPGD 0.141 −6.830 −5.781 FN1 0.147 1.594 1.186HNRNPL 0.156 −0.036 0.085 AIM2 0.159 −4.093 −4.610 MMP13 0.178 −7.096−8.365 BBC 0.179 −7.464 −7.738 EGFR 0.189 0.908 0.705 SPP1 0.200 −0.144−1.332 SERPINB4 0.251 −11.815 −10.852 NEFL 0.292 −2.876 −1.321 NFASC0.301 −3.832 −3.738 PI3 0.324 4.686 4.847 PIG3 0.333 −3.420 −3.698 LAMC20.350 0.480 0.196 ARPC2 0.353 −0.053 −0.006 AADAC 0.379 −16.094 −15.629IL24 0.387 −3.969 −4.629 S100A8 0.388 3.838 3.936 CCL27 0.398 −12.922−13.230 PTHLH 0.401 0.777 0.907 S100A9 0.457 7.525 7.534 DDAH1 0.461−5.660 −5.216 PDL1 0.471 −3.067 −3.124 DSS1 0.477 −5.722 −5.442 KRT190.486 −2.982 −3.853 KIT 0.529 −2.391 −2.415 TUBB3 0.599 −4.541 −5.167MYC 0.631 −3.816 −3.749 CHI3L1 0.653 −0.029 0.025 MMP9 0.684 1.649 1.733CXCR4 0.742 −8.733 −8.858 ATP6V0E2 0.750 −8.562 −8.519 CXCL10 0.785−3.039 −3.184 PD1 0.825 −1.878 −1.870 IL7R 0.872 −8.524 −8.094 MMP120.919 −2.958 −3.225 CEP76 0.981 −4.361 −4.656

TABLE 3 18 Genes included in a GEP signature able to predict recurrencein cSCC Gene symbol p-value mean - Recurrence mean - Non-RecurrenceACSBG1 0.024 −3.613 −2.489 ANXA9 0.050 −8.007 −7.059 APOBEC3G 0.035−3.800 −4.260 DCT 0.001 −5.696 −3.003 EphB2 0.001 −1.846 −2.648 FLG0.001 −4.104 −1.594 INHBA 0.016 −1.203 −2.222 KRT18 0.000 0.454 −1.081LCE2B 0.000 0.447 2.490 LOR 0.000 0.310 2.935 MMP1 0.014 2.290 0.970MMP3 0.006 −2.887 −5.159 MMP7 0.010 −3.915 −5.568 NEB 0.002 −3.495−2.807 NFIB 0.036 −2.623 −2.385 TFAP2B 0.001 −6.571 −3.836 TYRP1 0.006−5.869 −3.709 USP7 0.029 0.689 1.076

Example 3: Initial Training Set Development Studies and Comparison toValidation Cohort

R version 3.3.2 was used to train multiple predictive models (e.g.,multiple machine-learning methods such as, neural networks, gradientboosting machine, generalized linear model boost, radial basis function,rule-based classification, decision tree classification, and/orregularized linear discriminant analysis) against the normalized Ctvalues obtained from RT-PCR analysis in 181 cSCC cases selected atrandom from the 240 cases in the combined set. The average of the toppredictive models was more sensitive than either the Brigham and Women'sHospital (BWH) or American Joint Committee on Cancer (AJCC) models withminimal loss of specificity. These results show that recurrent andnon-recurrent cSCC can be identified through gene expression profilingand gene expression can be used to identify cSCC patients with a higherrisk of recurrence. A validated prognostic test could inform clinicaldecision-making on preoperative surgical staging (for example, based onshave biopsy), surgical approach (SLNB) or adjuvant radiation to reducelocal recurrence, and adjuvant radiation, nodal staging, adjuvantsystemic therapy to reduce regional/distant metastasis. Such a testcould improve such intervention decisions and help determine whichpatients may benefit from additional therapeutic modalities.

TABLE 4 Predictive modeling - local recurrence GEP Local RecurrenceExample 2 BWH AJCCv7 AJCCv8 Sensitivity 75% 17%  0% 39% Specificity 92%90% 99.5%  79% negative predictive value 98% 92% 92% 94% (NPV) positivepredictive value 50% 13% 94% 14% (PPV)

TABLE 5 Predictive modeling - metastasis GEP Regional/Distant MetastasisExample 2 BWH AJCCv7 AJCCv8 Sensitivity 83% 23% 0% 46% Specificity 95%90% 100%  79% negative predictive value 99% 95% 94%  96% (NPV) positivepredictive value 53% 13% 0% 12% (PPV)

Example 4: Prognostic Gene Expression Profile Test in cSCC in Patientswith One or More High-Risk Features

To identify a gene expression profile that accurately predicts: (1)primary cSCC with a high risk of regional nodal/distant metastasis; and(2) primary cSCC with high risk of local recurrence after completesurgical clearance, a multi-center study was performed using archivedprimary tissue samples with extensive capture of associated clinicaldata. The approach uses targeted candidate genes from the literaturecombined with genes from a global approach microarray screen. Samplesare from subjects with pathologically confirmed cSCC diagnosed after2006, minimum 3 years of follow-up or event (see Tables 6 and 7). Twoseparate outcomes were measured: (1) nodal/distant metastasis; and (2)local recurrence. Accuracy metrics demonstrate that the gene expressionsignature has prognostic value for in an independent cohort (see Table 8and FIG. 4). The prognostic test could inform clinical decision-makingon: (1) preoperative surgical staging, based on shave biopsy; and (2)adjuvant radiation, nodal staging, adjuvant systemic therapy to reduceregional/distant metastasis.

TABLE 6 Demographics for development stage of Example 4.Regional/distant All Non-Metastatic metastasis Feature (n = 122) (n =108) (n = 14) Age: Median years (range) 74 (49-97) 74 (50-97) 74.5(49-91) Definitive surgery: Mohs 99 (82%) ^(#) 88 (82%) ^(#) 11 (79%)Male sex 94 (77%) 81 (75%) 13 (93%) Patient immunocompromised 17 (14%)13 (12%) 4 (29%) Located on head or neck 87 (71%) 77 (71%) 10 (71%)Tumor diameter: Mean +/− SD 2.0 +/− 2.9 1.5 +/− 1.3 5.8 +/− 6.7***Differentiation Status: Poorly differentiated 5 (4%) 4 (4%) 1 (7%) ClarkLevel IV/V 45 (37%) 40 (37%) 5 (36%) Perineural invasion present 7 (6%)6 (6%) 1 (7%) Invasion into subcutaneous fat 7 (6%) 4 (4%) 3 (21%) **^(#) 1 case with unknown surgery type; Wilcoxon F or Chi-square test p** <0.01 ***<0.001

TABLE 7 Demographics for validation stage of Example 4. All Non-MetRegional/distant met Feature (n = 107) (n = 90) (n = 17) Age: Medianyears (range) 72 (30-93) 72.5 (45-93) 72 (30-88) Definitive surgery:Mohs 86 (81%)^(#) 76 (84%) 10 (63%)^(#)* Male sex 78 (73%) 64 (71%) 14(82%) Patient immunocompromised 12 (11%) 10 (11%) 2 (12%) Located onhead or neck 76 (71%) 62 (69%) 14 (82%) Tumor diameter: Mean +/− SD 1.9+/− 1.7 1.9 +/− 1.2 3.3 +/− 2.6** Differentiation Status: Poorlydifferentiated 13 (12%) 6 (7%) 7 (42%)*** Clark Level IV/V 32 (30%) 25(28%) 7 (41%) Perineural invasion present 9 (8%) 3 (3%) 6 (35%)***Invasion into subcutaneous fat 17 (16%) 11 (12%) 6 (35%)* ^(#)1 casewith unknown surgery type; Wilcoxon F or Chi-square test p *<0.05**<0.01 ***<0.001

TABLE 8 Predictive modeling GEP Metric Example 4 AJCC 8 BWH Sensitivity53% 53% 41% Specificity 93% 87% 88% negative predictive value 91% 91%89% (NPV) positive predictive value 60% 43% 39% (PPV)

Example 5: Prognostic Gene Expression Signature for Risk Assessment incSCC with a Subanalysis in the Head and Neck Region

To identify a gene expression profile that accurately predicts: (1)primary cSCC with a high risk of metastasis (regional nodal/distantmetastasis); and (2) primary cSCC with high risk of local recurrenceafter complete surgical clearance, a multi-center study was performedusing archived primary tissue samples with extensive capture ofassociated clinical data. The approach uses targeted candidate genesfrom the literature combined with genes from a global approachmicroarray screen. Samples are from subjects with pathologicallyconfirmed cSCC diagnosed after 2006, minimum 3 years of follow-up orevent (see Table 9). Two separate outcomes were measured: (1)nodal/distant metastasis; and (2) local recurrence. Accuracy metricsaccuracy metrics for all and head and neck cSCC cases suggest that geneexpression signature has prognostic value in an independent cohort (seeTable 10). The prognostic signature with a robust PPV for high-riskdisease will improve identification of patients with cSCC who canbenefit from surgical, radiation and immunotherapy interventions.

TABLE 9 Demographics - head and neck subanalysis Non- MetastaticMetastasis Feature of head and neck case (n = 34) (n = 9) Age: Medianyears (range) 75 (49-89) 77 (49-89) Definitive surgery: Mohs 33 (97%) 8(89%) Male sex 31 (91%) 8 (89%) Tumor diameter: Mean cm +/− SD 2.52 +/−1.35 5.89 +/− 8.36 Differentiation Status: Poor/Undifferentiated 2 (6%)2 (22%) Clark Level IV/V 4 (12%) 1 (11%) Perineural invasion present 4(12%) 0 (0%) Invasion into subcutaneous fat 7 (21%) 1 (11%)

TABLE 10 Predictive modeling - head and neck subanalysis All (n = 107)H&N (n = 76) GEP GEP Metric Example 5 BWH this study BWH Sensitivity 53%41% 43% 43% Specificity 93% 88% 94% 89% negative predictive value 91%89% 88% 87% (NPV) positive predictive value 60% 39% 60% 46% (PPV)

TABLE 11 Genes included in the gene sets that are able to predict riskof recurrence and/or metastasis median Probe Identifier median Non-delta Gene name (ThermoFisher) Recurrent Recurrent median * p-valueKRT6B Hs00745492_s1 5.522 7.091 −1.569 0.000070 LOR Hs01894962_s1 1.9704.492 −2.522 0.000265 FLG Hs00856927_g1 −2.724 0.303 −3.027 0.000291LCE2B Hs04194422_s1 1.153 3.665 −2.512 0.000809 PLS3 Hs00543973_m1−0.416 0.080 −0.497 0.001048 SERPINB2 Hs01010736_m1 0.304 1.455 −1.1500.001277 KLK5 Hs00202752_m1 1.170 3.239 −2.069 0.001468 KRT18Hs01920599_gH 0.975 −0.238 1.213 0.002094 BBC Hs00248075_m1 −4.614−5.334 0.720 0.002663 MIR3916 Hs04232205_s1 −0.709 −1.334 0.625 0.002734LOC100287896 Hs01931732_s1 −2.224 −2.796 0.572 0.003547 TFAP2BHs01560931_m1 −4.288 −2.456 −1.832 0.004135 HPGD Hs00960591_m1 −5.491−3.113 −2.378 0.007656 CHMP2B Hs00387770_m1 −3.117 −2.591 −0.5260.008827 ANXA9 Hs01070154_m1 −5.583 −4.284 −1.299 0.009038 ID2Hs00747379_m1 −0.345 0.493 −0.838 0.009695 EphB2 Hs00362096_m1 −1.124−1.614 0.491 0.012203 NEB Hs00189880_m1 −2.611 −1.904 −0.706 0.014937FDFT1 Hs00926053_m1 −1.589 −0.657 −0.932 0.017046 USP7 Hs00931763_m11.509 1.960 −0.452 0.017046 TAF6L Hs01008033_m1 −0.699 −0.961 0.2620.018195 ACSBG1 Hs01025572_m1 −2.992 −1.336 −1.657 0.026077 HNRNPLHs00704853_s1 0.776 0.980 −0.204 0.031337 ARPC2 Hs01031740_m1 0.7151.147 −0.432 0.031337 DUXAP8 Hs04942686_m1 −6.816 −9.507 2.691 0.039746PIM2 Hs01546752_g1 −1.160 −1.752 0.592 0.050944 KRT17 Hs00356958_m16.944 7.254 −0.310 0.053874 APOBEC3G Hs00222415_m1 −2.574 −3.024 0.4500.056942 DSS1 Hs00428732_m1 −4.131 −3.182 −0.949 0.056942 EGFRHs01076090_m1 1.598 1.332 0.266 0.069464 SERPINB4 Hs01691258_g1 −12.838−8.116 −4.722 0.070706 UGP2 Hs00900510_m1 −1.783 −1.437 −0.346 0.073246SPATA41 Hs03028557_s1 −12.073 −13.333 1.261 0.077195 SNORD124Hs03464469_s1 −2.848 −2.958 0.110 0.082729 PI3 Hs00964384_g1 5.550 6.140−0.589 0.085614 LIME1-ZGPAT Hs00738791_g1 −4.044 −4.312 0.267 0.090094MMP3 Hs00968305_m1 −1.478 −2.397 0.919 0.099619 S100A8 Hs00374264_g14.237 5.014 −0.777 0.104673 PTRHD1 Hs00415546_m1 −1.338 −1.216 −0.1220.109930 MMP7 Hs01042796_m1 −2.399 −3.937 1.538 0.115392 TMEM41BHs01379134_m1 −1.979 −1.562 −0.417 0.119151 SPP1 Hs00959010_m1 1.6500.427 1.224 0.121066 RBM33 Hs00997579_m1 1.600 1.349 0.251 0.152768 NFIBHs01029174_m1 −1.757 −1.633 −0.124 0.159806 NEFL Hs00196245_m1 −0.0690.561 −0.631 0.162206 NFIC Hs00232157_m1 −0.500 −0.300 −0.200 0.167086DCT Hs01098278_m1 −3.033 −1.300 −1.733 0.174613 RCHY1 Hs00996236_m1−1.807 −2.038 0.231 0.177178 ZSCAN31 Hs00372831_g1 −3.639 −2.926 −0.7130.179770 IPO5P1 Hs05052601_s1 −2.927 −3.231 0.303 0.179770 RUNX3Hs00231709_m1 −0.927 −1.342 0.415 0.204381 MKLN1 Hs00992679_m1 −0.787−0.930 0.144 0.204381 ATP6V0E2 Hs04189864_m1 −5.596 −6.247 0.6510.207260 YKT6 Hs00559914_m1 2.007 1.788 0.220 0.210168 FCHSD1Hs00703025_s1 −6.048 −5.195 −0.854 0.216073 MMP1 Hs00899658_m1 3.1562.381 0.774 0.225153 CEP76 Hs00950371_m1 −3.743 −3.455 −0.288 0.225153TUFM-MIR4721 Hs00944507_g1 2.465 2.281 0.184 0.228239 AIM2 Hs00915710_m1−2.525 −2.720 0.195 0.244123 PTHLH Hs00174969_m1 0.986 1.833 −0.8480.264188 BHLHB9 Hs01089557_s1 −14.090 −12.657 −1.433 0.264188 CD163Hs00174705_m1 −0.829 −1.156 0.327 0.307655 ZNF839 Hs00901350_g1 −1.060−1.316 0.256 0.307655 BLOC1S1 Hs00155241_m1 −1.061 −0.787 −0.2730.311480 HDDC3 Hs00826827_g1 −1.299 −1.567 0.267 0.319223 TNNC1Hs00896999_g1 −7.015 −5.911 −1.105 0.323141 S100A9 Hs00610058_m1 8.0718.385 −0.314 0.327091 TUBB3 Hs00801390_s1 −3.190 −2.711 −0.479 0.331071KIT Hs00174029_m1 −1.168 −1.574 0.406 0.351443 FN1 Hs01549976_m1 2.3021.859 0.443 0.364039 INHBA Hs01081598_m1 −1.107 −1.166 0.060 0.368299PIGBOS1 Hs05036222_s1 −0.970 −1.132 0.162 0.372591 THYN1 Hs01553775_g10.011 −0.219 0.230 0.376913 HOXA10- Hs00365956_m1 −3.574 −2.521 −1.0530.412594 HOXA9- MIR196B MYC Hs00153408_m1 −2.553 −2.337 −0.215 0.440624IL24 Hs01114274_m1 −3.039 −3.394 0.355 0.455038 NFIA Hs00379134_m1−0.852 −0.709 −0.143 0.499836 RPL26L1 Hs01631495_s1 −6.405 −6.603 0.1980.504954 ZNF48 Hs00399035_m1 −3.340 −3.577 0.237 0.520473 MIER2Hs00380101_m1 −0.275 −0.382 0.108 0.530953 MMP13 Hs00942584_m1 −4.547−5.058 0.511 0.536233 TYRP1 Hs00167051_m1 −2.547 −2.510 −0.037 0.546872VIM Hs00958111_m1 4.763 4.373 0.390 0.552231 LRRC47 Hs00975850_m1 0.1300.070 0.060 0.552231 ALOX12 Hs00167524_m1 −3.032 −2.563 −0.469 0.590445PLAU Hs01547054_m1 3.212 2.870 0.342 0.612814 IL7R Hs00902334_m1 −4.480−4.820 0.340 0.624137 DARS Hs00962398_m1 2.314 2.486 −0.172 0.624137LOC101927502 Hs05033260_s1 −8.529 −8.227 −0.302 0.624137 MIR129-1Hs03302824_pri −12.122 −13.033 0.910 0.647050 PD1 Hs00240906_m1 −1.233−1.099 −0.134 0.652832 CYP2D6- Hs03043789_g1 −5.343 −5.128 −0.2150.676166 LOC101929829 GTPBP2 Hs01051445_g1 −2.289 −2.127 −0.163 0.687952CXCL10 Hs00171042_m1 −1.850 −1.595 −0.255 0.693874 SLC1A3 Hs00904817_m1−2.518 −2.534 0.016 0.699815 RNF135 Hs00260480_m1 −0.694 −0.725 0.0300.711752 NOA1 Hs00260452_m1 −2.426 −2.528 0.102 0.747977 ZNF496Hs00262107_m1 −1.484 −1.549 0.065 0.760181 MMP12 Hs00159178_m1 −2.301−2.567 0.266 0.772445 C3orf70 Hs01395177_m1 −4.175 −4.227 0.052 0.784767LAMC2 Hs01043717_m1 0.874 1.000 −0.126 0.797143 MMP10 Hs00233987_m1−0.255 0.441 −0.696 0.803350 C1QL4 Hs00884853_s1 −10.397 −10.511 0.1130.822045 C21orf59 Hs00937509_m1 0.903 0.829 0.074 0.822045 KRT19Hs01051611_gH −3.414 −2.626 −0.788 0.828299 PDL1 Hs00204257_m1 −2.051−2.218 0.166 0.847127 SLC25A11 Hs01087946_g1 0.664 0.641 0.024 0.847127MRC1 Hs00267207_m1 −5.005 −5.020 0.015 0.853423 PIG3 Hs00936519_m1−3.104 −2.896 −0.207 0.853423 IL2RB Hs00386692_m1 −1.702 −1.592 −0.1100.878697 ATP6AP1 Hs05016463_s1 0.173 0.183 −0.011 0.878697 MSANTD4Hs00411188_g1 −3.627 −3.612 −0.015 0.929591 MRPL21 Hs00698959_m1 0.6650.664 0.002 0.929591 CXCR4 Hs00607978_s1 −5.555 −5.868 0.313 0.935977RPP38 Hs00705626_s1 −4.839 −4.719 −0.120 0.935977 SEPT3 Hs00251883_m1−5.165 −5.094 −0.071 0.942368 PDPN Hs00366766_m1 1.995 1.893 0.1020.948762 CCL27 Hs00171157_m1 −12.962 −11.407 −1.555 0.967963 CHI3L1Hs01072228_m1 0.794 0.689 0.105 0.974368 DDAH1 Hs00201707_m1 −3.775−3.568 −0.207 0.980774 MMP9 Hs00957562_m1 2.233 2.368 −0.135 0.987182NFASC Hs00978280_m1 −2.781 −2.716 −0.066 0.993591 * Positive valuesindicate an INCREASE in gene expression in recurrent cancer whencompared to non-recurrent control; and negative values indicate aDECREASE in gene expression in recurrent cancer when compared tonon-recurrent control.

TABLE 12 Accuracy of gene sets used to predict risk of recurrence and/ormetastasis Gene set Sensitivity Specificity PPV NPV AUC Kappa 20-10.4958 0.9481 0.5931 0.9370 0.8604 0.4537 20-2 0.5208 0.9333 0.58690.9385 0.8101 0.4524 20-3 0.4438 0.9472 0.5829 0.9292 0.8131 0.4147 20-40.4708 0.9324 0.5688 0.9318 0.8766 0.4084 20-5 0.4833 0.9324 0.49900.9335 0.8242 0.4033 20-6 0.4542 0.9389 0.5722 0.9306 0.8275 0.3991 20-70.5396 0.9065 0.4634 0.9395 0.8384 0.3934 20-8 0.3917 0.9537 0.59220.9238 0.7275 0.3783 20-9 0.4396 0.9259 0.5132 0.9274 0.8220 0.367320-10 0.3708 0.9556 0.5888 0.9228 0.7970 0.3621 20-11 0.4542 0.92410.4625 0.9299 0.7701 0.3615 20-12 0.4292 0.9324 0.4984 0.9280 0.78760.3613 20-13 0.3896 0.9472 0.5367 0.9234 0.8228 0.3605 20-14 0.41460.9343 0.5150 0.9254 0.7698 0.3600 20-15 0.4417 0.9278 0.4798 0.92990.7799 0.3553 20-16 0.4271 0.9278 0.4667 0.9262 0.7650 0.3506 20-170.4146 0.9287 0.4673 0.9248 0.7613 0.3506 20-18 0.4563 0.9139 0.45180.9297 0.8198 0.3491 20-19 0.4188 0.9315 0.5352 0.9270 0.8132 0.348920-20 0.4229 0.9296 0.4484 0.9264 0.7674 0.3438 20-21 0.4396 0.92310.4449 0.9290 0.8336 0.3420 20-22 0.4354 0.9194 0.4282 0.9268 0.81270.3418 20-23 0.3563 0.9537 0.5608 0.9213 0.7605 0.3379 20-24 0.38960.9296 0.4846 0.9221 0.7662 0.3357 20-25 0.3896 0.9370 0.4919 0.92180.8326 0.3354 30-1 0.4021 0.9648 0.6285 0.9275 0.8091 0.3893 30-2 0.47710.9204 0.4672 0.9335 0.8005 0.3739 30-3 0.4438 0.9287 0.4984 0.92870.8083 0.3685 30-4 0.4208 0.9306 0.5525 0.9270 0.8064 0.3613 30-5 0.40000.9407 0.5432 0.9255 0.7804 0.3513 30-6 0.4542 0.9167 0.4574 0.92880.7920 0.3480 30-7 0.3875 0.9407 0.5049 0.9240 0.8209 0.3378 30-8 0.37920.9454 0.5218 0.9225 0.7739 0.3375 30-9 0.3542 0.9593 0.5714 0.92070.6822 0.3347 30-10 0.4458 0.9157 0.4271 0.9281 0.7544 0.3339 30-110.4167 0.9213 0.4288 0.9245 0.7915 0.3329 30-12 0.3813 0.9380 0.47320.9216 0.7236 0.3318 30-13 0.3229 0.9565 0.6146 0.9170 0.7093 0.324330-14 0.3729 0.9361 0.4768 0.9222 0.7127 0.3187 30-15 0.4042 0.91760.3988 0.9225 0.7716 0.3103 30-16 0.3667 0.9306 0.4688 0.9195 0.71270.3052 30-17 0.3375 0.9426 0.4744 0.9178 0.6708 0.3025 30-18 0.38130.9213 0.4323 0.9205 0.8029 0.2996 30-19 0.4146 0.9102 0.3787 0.92410.7652 0.2984 30-20 0.3667 0.9296 0.4427 0.9199 0.7452 0.2954 30-210.3583 0.9306 0.4480 0.9197 0.7475 0.2900 30-22 0.3625 0.9241 0.46850.9181 0.7671 0.2897 30-23 0.3833 0.9194 0.3956 0.9199 0.7480 0.289130-24 0.3417 0.9380 0.4473 0.9187 0.7222 0.2885 30-25 0.3979 0.91200.3898 0.9221 0.7419 0.2868 40-1 0.4688 0.9481 0.6105 0.9334 0.81980.4340 40-2 0.4021 0.9435 0.5360 0.9242 0.7960 0.3565 40-3 0.3792 0.94260.5311 0.9230 0.7486 0.3354 40-4 0.3563 0.9509 0.5030 0.9200 0.74270.3325 40-5 0.4125 0.9278 0.4898 0.9257 0.8127 0.3300 40-6 0.3896 0.93610.4924 0.9235 0.7824 0.3294 40-7 0.3854 0.9324 0.4662 0.9219 0.74210.3248 40-8 0.3646 0.9398 0.5220 0.9212 0.7262 0.3228 40-9 0.3583 0.93800.5303 0.9199 0.7621 0.3189 40-10 0.3500 0.9472 0.4906 0.9201 0.70590.3161 40-11 0.3938 0.9222 0.4707 0.9225 0.7623 0.3143 40-12 0.34170.9500 0.5070 0.9188 0.7769 0.3115 40-13 0.3896 0.9296 0.4195 0.92330.7851 0.3047 40-14 0.3479 0.9407 0.4750 0.9178 0.8177 0.3036 40-150.3729 0.9269 0.4124 0.9206 0.6769 0.3034 40-16 0.3646 0.9343 0.42240.9200 0.7467 0.2989 40-17 0.3792 0.9222 0.4296 0.9204 0.7539 0.298340-18 0.3208 0.9435 0.5381 0.9152 0.6774 0.2980 40-19 0.3688 0.91940.4660 0.9192 0.6873 0.2940 40-20 0.3854 0.9204 0.4162 0.9224 0.82750.2939 40-21 0.3833 0.9167 0.3896 0.9215 0.7007 0.2904 40-22 0.36250.9185 0.4270 0.9177 0.6769 0.2904 40-23 0.3313 0.9343 0.4227 0.91600.6716 0.2836 40-24 0.3438 0.9407 0.4236 0.9193 0.6736 0.2799 40-250.3250 0.9389 0.4582 0.9160 0.6687 0.2774

TABLE 13 Exemplary gene sets used to predict risk of recurrence and/ormetastasis Gene Probe identifiers used for each gene set (probeidentifiers from ThermoFisher set Scientific). 20-1 “Hs00705626_s1”“Hs00248075_m1” “Hs01560931_m1” “Hs00167524_m1” “Hs00366766_m1”“Hs01051445_g1” “Hs00996236_m1” “Hs01089557_s1” “Hs00262107_m1”“Hs01931732_s1” “Hs00399035_m1” “Hs00231709_m1” “Hs00411188_g1”“Hs00978280_m1” “Hs00826827_g1” “Hs00232157_m1” “Hs00747379_m1”“Hs00233987_m1” “Hs01008033_m1” “Hs04194422_s1” 20-2 “Hs00884853_s1”“Hs01920599_gH” “Hs00996236_m1” “Hs00248075_m1” “Hs00167524_m1”“Hs00747379_m1” “Hs00942584_m1” “Hs01042796_m1” “Hs00964384_g1”“Hs05052601_s1” “Hs00356958_m1” “Hs00901350_g1” “Hs01691258_g1”“Hs00992679_m1” “Hs01051611_gH” “Hs04194422_s1” “Hs01089557_s1”“Hs01087946_g1” “Hs05036222_s1” “Hs00856927_g1” 20-3 “Hs00248075_m1”“Hs00251883_m1” “Hs01089557_s1” “Hs00356958_m1” “Hs00856927_g1”“Hs00202752_m1” “Hs00950371_m1” “Hs00899658_m1” “Hs00362096_m1”“Hs01043717_m1” “Hs01560931_m1” “Hs00826827_g1” “Hs01010736_m1”“Hs00167524_m1” “Hs01031740_m1” “Hs01920599_gH” “Hs00201707_m1”“Hs00738791_g1” “Hs00962398_m1” “Hs00543973_m1” 20-4 “Hs00962398_m1”“Hs01920599_gH” “Hs01025572_m1” “Hs00159178_m1” “Hs01089557_s1”“Hs00167524_m1” “Hs00248075_m1” “Hs00386692_m1” “Hs00856927_g1”“Hs00996236_m1” “Hs01031740_m1” “Hs01010736_m1” “Hs00900510_m1”“Hs00826827_g1” “Hs01008033_m1” “Hs00415546_m1” “Hs04942686_m1”“Hs00801390_s1” “Hs01072228_m1” “Hs01547054_m1” 20-5 “Hs00411188_g1”“Hs00248075_m1” “Hs00202752_m1” “Hs00747379_m1” “Hs01042796_m1”“Hs01920599_gH” “Hs01114274_m1” “Hs00942584_m1” “Hs00996236_m1”“Hs00167524_m1” “Hs00978280_m1” “Hs00543973_m1” “Hs00826827_g1”“Hs01560931_m1” “Hs00931763_m1” “Hs01089557_s1” “Hs00174029_m1”“Hs01029174_m1” “Hs00415546_m1” “Hs00964384_g1” 20-6 “Hs00975850_m1”“Hs04942686_m1” “Hs00202752_m1” “Hs00233987_m1” “Hs00926053_m1”“Hs00856927_g1” “Hs00992679_m1” “Hs00251883_m1” “Hs00415546_m1”“Hs00960591_m1” “Hs00901350_g1” “Hs00747379_m1” “Hs01089557_s1”“Hs00936519_m1” “Hs03043789_g1” “Hs0 1560931_m1” “Hs00232157_m1”“Hs00957562_m1” “Hs00248075_m1” “Hs01549976_m1” 20-7 “Hs04194422_s1”“Hs00262107_m1” “Hs01546752_g1” “Hs01920599_gH” “Hs04189864_m1”“Hs01089557_s1” “Hs01560931_m1” “Hs00705626_s1” “Hs01043717_m1”“Hs00747379_m1” “Hs00248075_m1” “Hs00856927_g1” “Hs01029174_m1”“Hs00543973_m1” “Hs01395177_m1” “Hs00260480_m1” “Hs00174029_m1”“Hs00387770_m1” “Hs01894962_s1” “Hs00745492_s1” 20-8 “Hs01560931_m1”“Hs00738791_g1” “Hs00856927_g1” “Hs00362096_m1” “Hs00826827_g1”“Hs01098278_m1” “Hs00975850_m1” “Hs00167524_m1” “Hs00260452_m1”“Hs04194422_s1” “Hs01043717_m1” “Hs00233987_m1” “Hs00703025_s1”“Hs00896999_g1” “Hs00167051_m1” “Hs00942584_m1” “Hs01087946_g1”“Hs00411188_g1” “Hs00747379_m1” “Hs05016463_s1” 20-9 “Hs00362096_m1”“Hs00942584_m1” “Hs01560931_m1” “Hs00167524_m1” “Hs00884853_s1”“Hs00248075_m1” “Hs01920599_gH” “Hs00996236_m1” “Hs00747379_m1”“Hs01089557_s1” “Hs00959010_m1” “Hs00372831_g1” “Hs04194422_s1”“Hs01043717_m1” “Hs00399035_m1” “Hs01051611_gH” “Hs01042796_m1”“Hs00968305_m1” “Hs00260452_m1” “Hs01031740_m1” 20-10 “Hs05033260_s1”“Hs00233987_m1” “Hs04194422_s1” “Hs00992679_m1” “Hs00926053_m1”“Hs00167524_m1” “Hs00202752_m1” “Hs01549976_m1” “Hs00415546_m1”“Hs01072228_m1” “Hs01691258_g1” “Hs00387770_m1” “Hs00380101_m1”“Hs00231709_m1” “Hs01920599_gH” “Hs00543973_m1” “Hs00386692_m1”“Hs00705626_s1” “Hs00196245_m1” “Hs01081598_m1” 20-11 “Hs01114274_m1”“Hs01560931_m1” “Hs00738791_g1” “Hs00931763_m1” “Hs00996236_m1”“Hs00362096_m1” “Hs00747379_m1” “Hs00411188_g1” “Hs00900510_m1”“Hs01098278_m1” “Hs00233987_m1” “Hs04194422_s1” “Hs00826827_g1”“Hs00856927_g1” “Hs00232157_m1” “Hs01010736_m1” “Hs00704853_s1”“Hs00959010_m1” “Hs00260480_m1” “Hs00915710_m1” 20-12 “Hs00992679_m1”“Hs00159178_m1” “Hs00167524_m1” “Hs00958111_m1” “Hs00901350_g1”“Hs00931763_m1” “Hs00233987_m1” “Hs01549976_m1” “Hs01894962_s1”“Hs01089557_s1” “Hs00171157_m1” “Hs00153408_m1” “Hs00248075_m1”“Hs03464469_s1” “Hs04194422_s1” “Hs00745492_s1” “Hs00366766_m1”“Hs00856927_g1” “Hs00957562_m1” “Hs01025572_m1” 20-13 “Hs01379134_m1”“Hs00362096_m1” “Hs05052601_s1” “Hs00959010_m1” “Hs00251883_m1”“Hs01089557_s1” “Hs00856927_g1” “Hs00167524_m1” “Hs00159178_m1”“Hs04942686_m1” “Hs00356958_m1” “Hs01042796_m1” “Hs03464469_s1”“Hs01029174_m1” “Hs00248075_m1” “Hs00610058_m1” “Hs01070154_m1”“Hs00703025_s1” “Hs00964384_g1” “Hs00705626_s1” 20-14 “Hs00362096_m1”“Hs00996236_m1” “Hs00931763_m1” “Hs01081598_m1” “Hs01560931_m1”“Hs00167524_m1” “Hs00543973_m1” “Hs01098278_m1” “Hs00856927_g1”“Hs03043789_g1” “Hs01089557_s1” “Hs01051445_g1” “Hs00747379_m1”“Hs01114274_m1” “Hs00826827_g1” “Hs00936519_m1” “Hs00960591_m1”“Hs00201707_m1” “Hs00899658_m1” “Hs04189864_m1” 20-15 “Hs00856927_g1”“Hs04942686_m1” “Hs00248075_m1” “Hs01029174_m1” “Hs00992679_m1”“Hs00975850_m1” “Hs03464469_s1” “Hs00167524_m1” “Hs01691258_g1”“Hs00960591_m1” “Hs01089557_s1” “Hs04194422_s1” “Hs01114274_m1”“Hs00901350_g1” “Hs00936519_m1” “Hs00233987_m1” “Hs00411188_g1”“Hs00900510_m1” “Hs00174969_m1” “Hs01070154_m1” 20-16 “Hs00826827_g1”“Hs00738791_g1” “Hs00698959_m1” “Hs00153408_m1” “Hs00167051_m1”“Hs00365956_m1” “Hs04194422_s1” “Hs00167524_m1” “Hs01560931_m1”“Hs00610058_m1” “Hs00232157_m1” “Hs00996236_m1” “Hs00705626_s1”“Hs00362096_m1” “Hs01098278_m1” “Hs00997579_m1” “Hs00559914_m1”“Hs00856927_g1” “Hs00944507_g1” “Hs00379134_m1” 20-17 “Hs00232157_m1”“Hs00543973_m1” “Hs05052601_s1” “Hs00196245_m1” “Hs01042796_m1”“Hs00411188_g1” “Hs00899658_m1” “Hs00374264_g1” “Hs01894962_s1”“Hs04194422_s1” “Hs03464469_s1” “Hs00992679_m1” “Hs00901350_g1”“Hs00362096_m1” “Hs00856927_g1” “Hs00167524_m1” “Hs01089557_s1”“Hs01931732_s1” “Hs01549976_m1” “Hs01395177_m1” 20-18 “Hs00884853_s1”“Hs00167524_m1” “Hs00978280_m1” “Hs00747379_m1” “Hs01931732_s1”“Hs00931763_m1” “Hs04942686_m1” “Hs04194422_s1” “Hs00856927_g1”“Hs00248075_m1” “Hs00901350_g1” “Hs00415546_m1” “Hs01089557_s1”“Hs01025572_m1” “Hs00231709_m1” “Hs00386692_m1” “Hs01920599_gH”“Hs00202752_m1” “Hs01029174_m1” “Hs00942584_m1” 20-19 “Hs01547054_m1”“Hs00960591_m1” “Hs03464469_s1” “Hs01560931_m1” “Hs00153408_m1”“Hs00233987_m1” “Hs01089557_s1” “Hs00366766_m1” “Hs00248075_m1”“Hs01010736_m1” “Hs00251883_m1” “Hs00996236_m1” “Hs00610058_m1”“Hs00900510_m1” “Hs01008033_m1” “Hs00978280_m1” “Hs00260452_m1”“Hs04194422_s1” “Hs00196245_m1” “Hs05052601_s1” 20-20 “Hs01098278_m1”“Hs01072228_m1” “Hs01691258_g1” “Hs00387770_m1” “Hs00543973_m1”“Hs01920599_gH” “Hs04189864_m1” “Hs05033260_s1” “Hs00856927_g1”“Hs00366766_m1” “Hs03043789_g1” “Hs04194422_s1” “Hs00202752_m1”“Hs00936519_m1” “Hs01560931_m1” “Hs00958111_m1” “Hs00251883_m1”“Hs00704853_s1” “Hs00738791_g1” “Hs00962398_m1” 20-21 “Hs01042796_m1”“Hs01560931_m1” “Hs00884853_s1” “Hs00958111_m1” “Hs00411188_g1”“Hs05052601_s1” “Hs01920599_gH” “Hs00248075_m1” “Hs00747379_m1”“Hs00996236_m1” “Hs00251883_m1” “Hs00202752_m1” “Hs01008033_m1”“Hs00201707_m1” “Hs01051445_g1” “Hs00950371_m1” “Hs01029174_m1”“Hs00232157_m1” “Hs01087946_g1” “Hs00267207_m1” 20-22 “Hs00559914_m1”“Hs00856927_g1” “Hs00978280_m1” “Hs01920599_gH” “Hs01560931_m1”“Hs00365956_m1” “Hs00610058_m1” “Hs01008033_m1” “Hs04194422_s1”“Hs00975850_m1” “Hs00204257_m1” “Hs00950371_m1” “Hs00705626_s1”“Hs01089557_s1” “Hs00196245_m1” “Hs01042796_m1” “Hs00174029_m1”“Hs01546752_g1” “Hs01098278_m1” “Hs00231709_m1” 20-23 “Hs04194422_s1”“Hs01089557_s1” “Hs00155241_m1” “Hs00942584_m1” “Hs05033260_s1”“Hs01546752_g1” “Hs01920599_gH” “Hs01560931_m1” “Hs00387770_m1”“Hs00399035_m1” “Hs00232157_m1” “Hs00931763_m1” “Hs00231709_m1”“Hs00856927_g1” “Hs00233987_m1” “Hs01098278_m1” “Hs00978280_m1”“Hs04942686_m1” “Hs00411188_g1” “Hs00201707_m1” 20-24 “Hs00232157_m1”“Hs01010736_m1” “Hs00704853_s1” “Hs00167051_m1” “Hs00738791_g1”“Hs00975850_m1” “Hs00362096_m1” “Hs00826827_g1” “Hs00233987_m1”“Hs00950371_m1” “Hs00204257_m1” “Hs01560931_m1” “Hs00196245_m1”“Hs01042796_m1” “Hs00174029_m1” “Hs00705626_s1” “Hs00856927_g1”“Hs01051445_g1” “Hs00399035_m1” “Hs05036222_s1” 20-25 “Hs00233987_m1”“Hs00380101_m1” “Hs00167524_m1” “Hs04189864_m1” “Hs00543973_m1”“Hs01920599_gH” “Hs00856927_g1” “Hs00155241_m1” “Hs01098278_m1”“Hs00703025_s1” “Hs00231709_m1” “Hs00365956_m1” “Hs00204257_m1”“Hs01395177_m1” “Hs00968305_m1” “Hs00374264_g1” “Hs00248075_m1”“Hs00202752_m1” “Hs00801390_s1” “Hs03464469_s1” 30-1 “Hs00387770_m1”“Hs00155241_m1” “Hs00251883_m1” “Hs01560931_m1” “Hs00428732_m1”“Hs00992679_m1” “Hs00705626_s1” “Hs00356958_m1” “Hs00960591_m1”“Hs00171157_m1” “Hs01072228_m1” “Hs01051445_g1” “Hs00232157_m1”“Hs00233987_m1” “Hs04232205_s1” “Hs00559914_m1” “Hs00931763_m1”“Hs00167524_m1” “Hs00171042_m1” “Hs01089557_s1” “Hs04194422_s1”“Hs03464469_s1” “Hs00944507_g1” “Hs00196245_m1” “Hs00950371_m1”“Hs01395177_m1” “Hs01070154_m1” “Hs01051611_gH” “Hs00399035_m1”“Hs00703025_s1” 30-2 “Hs00937509_m1” “Hs00379134_m1” “Hs00899658_m1”“Hs00248075_m1” “Hs01920599_gH” “Hs04194422_s1” “Hs03043789_g1”“Hs00610058_m1” “Hs01089557_s1” “Hs00705626_s1” “Hs00362096_m1”“Hs01560931_m1” “Hs00233987_m1” “Hs00372831_g1” “Hs01072228_m1”“Hs01379134_m1” “Hs01076090_m1” “Hs04189864_m1” “Hs00957562_m1”“Hs01931732_s1” “Hs00856927_g1” “Hs01546752_g1” “Hs00171157_m1”“Hs00992679_m1” “Hs00931763_m1” “Hs00411188_g1” “Hs01008033_m1”“Hs00387770_m1” “Hs00996236_m1” “Hs00231709_m1” 30-3 “Hs00411188_g1”“Hs01395177_m1” “Hs01560931_m1” “Hs00379134_m1” “Hs00960591_m1”“Hs00745492_s1” “Hs00232157_m1” “Hs00899658_m1” “Hs00248075_m1”“Hs01010736_m1” “Hs00167524_m1” “Hs01691258_g1” “Hs00260452_m1”“Hs01070154_m1” “Hs00196245_m1” “Hs00747379_m1” “Hs01547054_m1”“Hs00950371_m1” “Hs00962398_m1” “Hs01087946_g1” “Hs00262107_m1”“Hs00260480_m1” “Hs00978280_m1” “Hs00428732_m1” “Hs00944507_g1”“Hs00387770_m1” “Hs00399035_m1” “Hs00738791_g1” “Hs00698959_m1”“Hs01549976 m1” 30-4 “Hs00415546_m1” “Hs00705626_s1” “Hs00204257_m1”“Hs00174969_m1” “Hs00745492_s1” “Hs01920599_gH” “Hs00387770_m1”“Hs01560931_m1” “Hs00958111_m1” “Hs01076090_m1” “Hs00379134_m1”“Hs00196245_m1” “Hs00232157_m1” “Hs01549976_m1” “Hs00801390_s1”“Hs00399035_m1” “Hs01089557_s1” “Hs00607978_s1” “Hs00960591_m1”“Hs00171157_m1” “Hs05033260_s1” “Hs00233987_m1” “Hs00904817_m1”“Hs01031740_m1” “Hs05016463_s1” “Hs00153408_m1” “Hs00968305_m1”“Hs00174029_m1” “Hs00944507_g1” “Hs00248075_m1” 30-5 “Hs05033260_s1”“Hs00362096_m1” “Hs00559914_m1” “Hs01560931_m1” “Hs00968305_m1”“Hs00931763_m1” “Hs04942686_m1” “Hs01920599_gH” “Hs00899658_m1”“Hs00248075_m1” “Hs00958111_m1” “Hs05016463_s1” “Hs03464469_s1”“Hs01931732_s1” “Hs01076090_m1” “Hs00992679_m1” “Hs00901350_g1”“Hs00937509_m1” “Hs00960591_m1” “Hs01114274_m1” “Hs01043717_m1”“Hs00167524_m1” “Hs01089557_s1” “Hs00204257_m1” “Hs00703025_s1”“Hs01549976_m1” “Hs01031740_m1” “Hs00262107_m1” “Hs00957562_m1”“Hs01029174_m1” 30-6 “Hs00958111_m1” “Hs00411188_g1” “Hs05036222_s1”“Hs00386692_m1” “Hs00745492_s1” “Hs01010736_m1” “Hs00997579_m1”“Hs00222415_m1” “Hs03464469_s1” “Hs00233987_m1” “Hs01547054_m1”“Hs00202752_m1” “Hs01025572_m1” “Hs00379134_m1” “Hs04194422_s1”“Hs00926053_m1” “Hs01560931_m1” “Hs00705626_s1” “Hs01920599_gH”“Hs00171042_m1” “Hs03043789_g1” “Hs00610058_m1” “Hs01089557_s1”“Hs00362096_m1” “Hs00380101_m1” “Hs00899658_m1” “Hs00801390_s1”“Hs00374264_g1” “Hs00964384_g1” “Hs00240906_m1” 30-7 “Hs00704853_s1”“Hs01560931_m1” “Hs01379134_m1” “Hs00958111_m1” “Hs00386692_m1”“Hs04942686_m1” “Hs00747379_m1” “Hs00167524_m1” “Hs03302824_pri”“Hs00248075_m1” “Hs00387770_m1” “Hs00978280_m1” “Hs00379134_m1”“Hs00233987_m1” “Hs00992679_m1” “Hs01931732_s1” “Hs00380101_m1”“Hs00705626_s1” “Hs00155241_m1” “Hs05033260_s1” “Hs01089557_s1”“Hs00171157_m1” “Hs00745492_s1” “Hs00937509_m1” “Hs00374264_g1”“Hs00240906_m1” “Hs01098278_m1” “Hs00174705_m1” “Hs00260480_m1”“Hs00372831_g1” 30-8 “Hs00202752_m1” “Hs00231709_m1” “Hs00366766_m1”“Hs00201707_m1” “Hs00826827_g1” “Hs00856927_g1” “Hs00174969_m1”“Hs00387770_m1” “Hs00167524_m1” “Hs01031740_m1” “Hs03464469_s1”“Hs01025572_m1” “Hs00996236_m1” “Hs00950371_m1” “Hs00610058_m1”“Hs01920599_gH” “Hs01051445_g1” “Hs00975850_m1” “Hs00978280_m1”“Hs00167051_m1” “Hs01560931_m1” “Hs00704853_s1” “Hs00902334_m1”“Hs01553775_g1” “Hs00962398_m1” “Hs01098278_m1” “Hs00356958_m1”“Hs01087946_g1” “Hs01029174_m1” “Hs007473 79_m1” 30-9 “Hs00362096_m1”“Hs01560931_m1” “Hs04942686_m1” “Hs05033260_s1” “Hs00958111_m1”“Hs00232157_m1” “Hs00899658_m1” “Hs00607978_s1” “Hs01549976_m1”“Hs00262107_m1” “Hs00968305_m1” “Hs00233987_m1” “Hs00904817_m1”“Hs00356958_m1” “Hs00900510_m1” “Hs00174969_m1” “Hs04194422_s1”“Hs01043717_m1” “Hs00745492_s1” “Hs00171042_m1” “Hs00379134_m1”“Hs00559914_m1” “Hs04232205_s1” “Hs00957562_m1” “Hs00167051_m1”“Hs05052601_s1” “Hs00380101_m1” “Hs01546752_g1” “Hs00801390_s1”“Hs01070154_m1” 30-10 “Hs00380101_m1” “Hs03464469_s1” “Hs00372831_g1”“Hs05052601_s1” “Hs04189864_m1” “Hs00248075_m1” “Hs00968305_m1”“Hs04942686_m1” “Hs00159178_m1” “Hs00386692_m1” “Hs00937509_m1”“Hs00960591_m1” “Hs00543973_m1” “Hs01894962_s1” “Hs00233987_m1”“Hs01051445_g1” “Hs01560931_m1” “Hs01089557_s1” “Hs00232157_m1”“Hs00387770_m1” “Hs01025572_m1” “Hs01395177_m1” “Hs00801390_s1”“Hs00884853_s1” “Hs01072228_m1” “Hs00201707_m1” “Hs00996236_m1”“Hs01114274_m1” “Hs00747379_m1” “Hs00167051_m1” 30-11 “Hs00801390_s1”“Hs01920599_gH” “Hs00931763_m1” “Hs00262107_m1” “Hs04942686_m1”“Hs00233987_m1” “Hs00399035_m1” “Hs00248075_m1” “Hs00171157_m1”“Hs00167524_m1” “Hs00899658_m1” “Hs00232157_m1” “Hs00362096_m1”“Hs00915710_m1” “Hs00174969_m1” “Hs00900510_m1” “Hs00387770_m1”“Hs00428732_m1” “Hs00607978_s1” “Hs00380101_m1” “Hs00260480_m1”“Hs00996236_m1” “Hs00958111_m1” “Hs01070154_m1” “Hs00543973_m1”“Hs00937509_m1” “Hs01089557_s1” “Hs00968305_m1” “Hs01072228_m1”“Hs01042796_m1” 30-12 “Hs00745492_s1” “Hs00950371_m1” “Hs00233987_m1”“Hs01560931_m1” “Hs00379134_m1” “Hs00167524_m1” “Hs00826827_g1”“Hs00978280_m1” “Hs00904817_m1” “Hs00856927_g1” “Hs00899658_m1”“Hs01008033_m1” “Hs00931763_m1” “Hs00365956_m1” “Hs03302824_pri”“Hs00428732_m1” “Hs00975850_m1” “Hs01894962_s1” “Hs00703025_s1”“Hs01072228_m1” “Hs01098278_m1” “Hs00958111_m1” “Hs00944507_g1”“Hs01010736_m1” “Hs00996236_m1” “Hs01920599_gH” “Hs00387770_m1”“Hs01547054_m1” “Hs00610058_m1” “Hs01087946_g1” 30-13 “Hs00856927_g1”“Hs00915710_m1” “Hs00379134_m1” “Hs00233987_m1” “Hs01008033_m1”“Hs00167524_m1” “Hs00899658_m1” “Hs00559914_m1” “Hs00904817_m1”“Hs04942686_m1” “Hs00386692_m1” “Hs00704853_s1” “Hs00978280_m1”“Hs00415546_m1” “Hs00399035_m1” “Hs00374264_g1” “Hs01560931_m1”“Hs01546752_g1” “Hs00231709_m1” “Hs00387770_m1” “Hs00964384_g1”“Hs00698959_m1” “Hs00196245_m1” “Hs01395177_m1” “Hs01076090_m1”“Hs00201707_m1” “Hs03302824_pri” “Hs00703025_s1” “Hs01114274_m1”“Hs01631495_s1” 30-14 “Hs00380101_m1” “Hs00232157_m1” “Hs00428732_m1”“Hs03302824_pri” “Hs01031740_m1” “Hs00171042_m1” “Hs01549976_m1”“Hs00260452_m1” “Hs00745492_s1” “Hs00411188_g1” “Hs00167524_m1”“Hs01560931_m1” “Hs00356958_m1” “Hs00559914_m1” “Hs00262107_m1”“Hs03464469_s1” “Hs00801390_s1” “Hs00202752_m1” “Hs00233987_m1”“Hs00196245_m1” “Hs00960591_m1” “Hs01546752_g1” “Hs01087946_g1”“Hs01547054_m1” “Hs00260480_m1” “Hs01070154_m1” “Hs00267207_m1”“Hs00174705_m1” “Hs00747379_m1” “Hs00387770_m1” 30-15 “Hs00960591_m1”“Hs00231709_m1” “Hs00251883_m1” “Hs00387770_m1” “Hs00356958_m1”“Hs00196245_m1” “Hs00174969_m1” “Hs00996236_m1” “Hs00559914_m1”“Hs00962398_m1” “Hs00856927_g1” “Hs00826827_g1” “Hs01025572_m1”“Hs00801390_s1” “Hs03043789_g1” “Hs00950371_m1” “Hs00233987_m1”“Hs00202752_m1” “Hs00260480_m1” “Hs00944507_g1” “Hs00978280_m1”“Hs01894962_s1” “Hs00204257_m1” “Hs00174029_m1” “Hs00703025_s1”“Hs01051611_gH” “Hs00958111_m1” “Hs00262107_m1” “Hs00167524_m1”“Hs01098278_m1” 30-16 “Hs00944507_g1” “Hs05016463_s1” “Hs03464469_s1”“Hs00167051_m1” “Hs00900510_m1” “Hs00904817_m1” “Hs04232205_s1”“Hs00356958_m1” “Hs00957562_m1” “Hs00745492_s1” “Hs00931763_m1”“Hs01043717_m1” “Hs00167524_m1” “Hs00856927_g1” “Hs00992679_m1”“Hs00380101_m1” “Hs01549976_m1” “Hs00559914_m1” “Hs01560931_m1”“Hs01098278_m1” “Hs00703025_s1” “Hs00248075_m1” “Hs01081598_m1”“Hs00428732_m1” “Hs00968305_m1” “Hs00705626_s1” “Hs00386692_m1”“Hs00174705_m1” “Hs00251883_m1” “Hs00415546_m1” 30-17 “Hs00543973_m1”“Hs00159178_m1” “Hs01098278_m1” “Hs00399035_m1” “Hs01029174_m1”“Hs00705626_s1” “Hs03302824_pri” “Hs01051611_gH” “Hs05033260_s1”“Hs01560931_m1” “Hs00167524_m1” “Hs01042796_m1” “Hs05052601_s1”“Hs00944507_g1” “Hs00978280_m1” “Hs00747379_m1” “Hs00171042_m1”“Hs00251883_m1” “Hs00960591_m1” “Hs01072228_m1” “Hs03043789_g1”“Hs00233987_m1” “Hs04942686_m1” “Hs00801390_s1” “Hs00992679_m1”“Hs01010736_m1” “Hs00232157_m1” “Hs00896999_g1” “Hs00826827_g1”“Hs00231709_m1” 30-18 “Hs01920599_gH” “Hs00248075_m1” “Hs00411188_g1”“Hs01560931_m1” “Hs00900510_m1” “Hs00996236_m1” “Hs00745492_s1”“Hs00202752_m1” “Hs00233987_m1” “Hs00222415_m1” “Hs01089557_s1”“Hs05052601_s1” “Hs00960591_m1” “Hs00958111_m1” “Hs01379134_m1”“Hs00380101_m1” “Hs00856927_g1” “Hs04189864_m1” “Hs01031740_m1”“Hs01042796_m1” “Hs01098278_m1” “Hs01395177_m1” “Hs00950371_m1”“Hs01691258_g1” “Hs00899658_m1” “Hs00962398_m1” “Hs00240906_m1”“Hs00399035_m1” “Hs00428732_m1” “Hs04942686_m1” 30-19 “Hs00428732_m1”“Hs01560931_m1” “Hs01025572_m1” “Hs00232157_m1” “Hs01089557_s1”“Hs01043717_m1” “Hs00705626_s1” “Hs00884853_s1” “Hs00543973_m1”“Hs00992679_m1” “Hs00899658_m1” “Hs00233987_m1” “Hs00745492_s1”“Hs01031740_m1” “Hs01076090_m1” “Hs00260480_m1” “Hs00856927_g1”“Hs00189880_m1” “Hs00231709_m1” “Hs01920599_gH” “Hs00171042_m1”“Hs00415546_m1” “Hs01894962_s1” “Hs04189864_m1” “Hs00174969_m1”“Hs00610058_m1” “Hs00153408_m1” “Hs01379134_m1” “Hs00915710_m1”“Hs01395177_m1” 30-20 “Hs00267207_m1” “Hs00366766_m1” “Hs04942686_m1”“Hs00231709_m1” “Hs01098278_m1” “Hs05016463_s1” “Hs00155241_m1”“Hs00900510_m1” “Hs00975850_m1” “Hs04194422_s1” “Hs01114274_m1”“Hs01072228_m1” “Hs01089557_s1” “Hs00747379_m1” “Hs00944507_g1”“Hs00705626_s1” “Hs00202752_m1” “Hs00978280_m1” “Hs01920599_gH”“Hs00196245_m1” “Hs04189864_m1” “Hs01025572_m1” “Hs05052601_s1”“Hs00380101_m1” “Hs01081598_m1” “Hs00372831_g1” “Hs00167051_m1”“Hs00232157_m1” “Hs01553775_g1” “Hs00738791_g1” 30-21 “Hs00174705_m1”“Hs01042796_m1” “Hs00856927_g1” “Hs00372831_g1” “Hs03302824_pri”“Hs05033260_s1” “Hs04189864_m1” “Hs00992679_m1” “Hs01560931_m1”“Hs00159178_m1” “Hs00196245_m1” “Hs05052601_s1” “Hs01031740_m1”“Hs00233987_m1” “Hs00975850_m1” “Hs01098278_m1” “Hs00248075_m1”“Hs00167524_m1” “Hs00171042_m1” “Hs01920599_gH” “Hs00380101_m1”“Hs00559914_m1” “Hs04942686_m1” “Hs00202752_m1” “Hs00937509_m1”“Hs00978280_m1” “Hs00936519_m1” “Hs00222415_m1” “Hs00365956_m1”“Hs00379134_m1” 30-22 “Hs00380101_m1” “Hs00233987_m1” “Hs00171042_m1”“Hs00411188_g1” “Hs00248075_m1” “Hs00559914_m1” “Hs00826827_g1”“Hs01894962_s1” “Hs01098278_m1” “Hs00232157_m1” “Hs01920599_gH”“Hs00975850_m1” “Hs00356958_m1” “Hs00543973_m1” “Hs01029174_m1”“Hs00159178_m1” “Hs05052601_s1” “Hs04194422_s1” “Hs01025572_m1”“Hs00950371_m1” “Hs00167524_m1” “Hs01072228_m1” “Hs00900510_m1”“Hs00705626_s1” “Hs01114274_m1” “Hs00904817_m1” “Hs00231709_m1”“Hs00745492_s1” “Hs00155241_m1” “Hs01081598_m1” 30-23 “Hs00964384_g1”“Hs00899658_m1” “Hs00374264_g1” “Hs00399035_m1” “Hs00703025_s1”“Hs00415546_m1” “Hs00232157_m1” “Hs00387770_m1” “Hs00826827_g1”“Hs01395177_m1” “Hs00202752_m1” “Hs00171042_m1” “Hs00996236_m1”“Hs00937509_m1” “Hs05016463_s1” “Hs00233987_m1” “Hs01114274_m1”“Hs01042796_m1” “Hs00248075_m1” “Hs00957562_m1” “Hs00196245_m1”“Hs01560931_m1” “Hs01089557_s1” “Hs00222415_m1” “Hs04194422_s1”“Hs01931732_s1” “Hs00884853_s1” “Hs00978280_m1” “Hs00959010_m1”“Hs00559914_m1” 30-24 “Hs01042796_m1” “Hs00801390_s1” “Hs00960591_m1”“Hs00992679_m1” “Hs00978280_m1” “Hs00937509_m1” “Hs01931732_s1”“Hs01560931_m1” “Hs05016463_s1” “Hs00171157_m1” “Hs00167524_m1”“Hs00260452_m1” “Hs01089557_s1” “Hs00232157_m1” “Hs00899658_m1”“Hs00904817_m1” “Hs00202752_m1” “Hs00958111_m1” “Hs00968305_m1”“Hs00248075_m1” “Hs00607978_s1” “Hs04942686_m1” “Hs01920599_gH”“Hs00365956_m1” “Hs00944507_g1” “Hs01043717_m1” “Hs00745492_s1”“Hs00704853_s1” “Hs00610058_m1” “Hs04194422_s1” 30-25 “Hs00738791_g1”“Hs04232205_s1” “Hs00362096_m1” “Hs00260452_m1” “Hs01547054_m1”“Hs00196245_m1” “Hs01560931_m1” “Hs00964384_g1” “Hs00415546_m1”“Hs00202752_m1” “Hs03043789_g1” “Hs00997579_m1” “Hs00745492_s1”“Hs00174029_m1” “Hs04194422_s1” “Hs00899658_m1” “Hs00251883_m1”“Hs00915710_m1” “Hs01042796_m1” “Hs04942686_m1” “Hs00248075_m1”“Hs00222415_m1” “Hs01081598_m1” “Hs01089557_s1” “Hs00705626_s1”“Hs00356958_m1” “Hs00204257_m1” “Hs00926053_m1” “Hs05052601_s1”“Hs00372831_g1” 40-1 “Hs00262107_m1” “Hs01560931_m1” “Hs00159178_m1”“Hs00975850_m1” “Hs00366766_m1” “Hs00543973_m1” “Hs00231709_m1”“Hs00372831_g1” “Hs00745492_s1” “Hs01072228_m1” “Hs04194422_s1”“Hs00174029_m1” “Hs00171157_m1” “Hs01029174_m1” “Hs01089557_s1”“Hs00801390_s1” “Hs00958111_m1” “Hs01098278_m1” “Hs01920599_gH”“Hs00233987_m1” “Hs00374264_g1” “Hs04189864_m1” “Hs00155241_m1”“Hs00610058_m1” “Hs03464469_s1” “Hs00386692_m1” “Hs00964384_g1”“Hs01025572_m1” “Hs01546752_g1” “Hs01395177_m1” “Hs00248075_m1”“Hs00937509_m1” “Hs00704853_s1” “Hs03028557_s1” “Hs00747379_m1”“Hs00904817_m1” “Hs00362096_m1” “Hs01087946_g1” “Hs01031740_m1”“Hs00978280_m1” 40-2 “Hs00231709_m1” “Hs01098278_m1” “Hs00174969_m1”“Hs01029174_m1” “Hs05036222_s1” “Hs00262107_m1” “Hs00856927_g1”“Hs05052601_s1” “Hs00233987_m1” “Hs00559914_m1” “Hs01931732_s1”“Hs01560931_m1” “Hs00167524_m1” “Hs00543973_m1” “Hs01010736_m1”“Hs00174029_m1” “Hs00260480_m1” “Hs00996236_m1” “Hs00745492_s1”“Hs00204257_m1” “Hs00374264_g1” “Hs04942686_m1” “Hs00411188_g1”“Hs00380101_m1” “Hs01051611_gH” “Hs01089557_s1” “Hs00901350_g1”“Hs01081598_m1” “Hs00738791_g1” “Hs01025572_m1” “Hs00248075_m1”“Hs01894962_s1” “Hs00957562_m1” “Hs00189880_m1” “Hs00937509_m1”“Hs00362096_m1” “Hs00962398_m1” “Hs00171042_m1” “Hs01076090_m1”“Hs00801390_s1” 40-3 “Hs00978280_m1” “Hs00900510_m1” “Hs00411188_g1”“Hs00174969_m1” “Hs00171157_m1” “Hs01546752_g1” “Hs04194422_s1”“Hs00826827_g1” “Hs01010736_m1” “Hs01043717_m1” “Hs00931763_m1”“Hs01089557_s1” “Hs00703025_s1” “Hs00559914_m1” “Hs03302824_pri”“Hs01087946_g1” “Hs00950371_m1” “Hs01051445_g1” “Hs00202752_m1”“Hs00380101_m1” “Hs01553775_g1” “Hs00232157_m1” “Hs00698959_m1”“Hs01098278_m1” “Hs03464469_s1” “Hs00884853_s1” “Hs00926053_m1”“Hs00936519_m1” “Hs00745492_s1” “Hs01560931_m1” “Hs00362096_m1”“Hs00204257_m1” “Hs00240906_m1” “Hs00366766_m1” “Hs00260480_m1”“Hs01549976_m1” “Hs00997579_m1” “Hs00738791_g1” “Hs01114274_m1”“Hs03043789_g1” 40-4 “Hs00899658_m1” “Hs00543973_m1” “Hs00260452_m1”“Hs00233987_m1” “Hs03302824_pri” “Hs04189864_m1” “Hs01089557_s1”“Hs05036222_s1” “Hs00428732_m1” “Hs00374264_g1” “Hs00958111_m1”“Hs00167524_m1” “Hs00856927_g1” “Hs00964384_g1” “Hs00900510_m1”“Hs00747379_m1” “Hs01087946_g1” “Hs05033260_s1” “Hs00607978_s1”“Hs04942686_m1” “Hs00937509_m1” “Hs00380101_m1” “Hs00386692_m1”“Hs00155241_m1” “Hs01114274_m1” “Hs03028557_s1” “Hs00240906_m1”“Hs01546752_g1” “Hs00975850_m1” “Hs00610058_m1” “Hs01631495_s1”“Hs00174029_m1” “Hs00411188_g1” “Hs00559914_m1” “Hs03043789_g1”“Hs00698959_m1” “Hs00703025_s1” “Hs00745492_s1” “Hs00387770_m1”“Hs01008033_m1” 40-5 “Hs00607978_s1” “Hs01031740_m1” “Hs00174969_m1”“Hs01114274_m1” “Hs04942686_m1” “Hs00931763_m1” “Hs00996236_m1”“Hs01395177_m1” “Hs01098278_m1” “Hs00387770_m1” “Hs04194422_s1”“Hs00248075_m1” “Hs01546752_g1” “Hs00705626_s1” “Hs01920599_gH”“Hs00801390_s1” “Hs05052601_s1” “Hs00960591_m1” “Hs01076090_m1”“Hs00232157_m1” “Hs00262107_m1” “Hs00944507_g1” “Hs00174705_m1”“Hs01089557_s1” “Hs01029174_m1” “Hs01051445_g1” “Hs00362096_m1”“Hs00399035_m1” “Hs00745492_s1” “Hs00978280_m1” “Hs01043717_m1”“Hs03028557_s1” “Hs00233987_m1” “Hs00704853_s1” “Hs01008033_m1”“Hs00543973_m1” “Hs00251883_m1” “Hs01691258_g1” “Hs00155241_m1”“Hs01042796_m1” 40-6 “Hs01931732_s1” “Hs00174705_m1” “Hs00248075_m1”“Hs00174969_m1” “Hs00950371_m1” “Hs00374264_g1” “Hs00232157_m1”“Hs00747379_m1” “Hs00884853_s1” “Hs00411188_g1” “Hs01089557_s1”“Hs00196245_m1” “Hs01029174_m1” “Hs01560931_m1” “Hs00379134_m1”“Hs04942686_m1” “Hs00738791_g1” “Hs00960591_m1” “Hs00171042_m1”“Hs05016463_s1” “Hs01025572_m1” “Hs00260480_m1” “Hs00428732_m1”“Hs00705626_s1” “Hs01114274_m1” “Hs00153408_m1” “Hs00944507_g1”“Hs00171157_m1” “Hs00962398_m1” “Hs00975850_m1” “Hs00997579_m1”“Hs00931763_m1” “Hs01379134_m1” “Hs04194422_s1” “Hs00703025_s1”“Hs01553775_g1” “Hs00365956_m1” “Hs01098278_m1” “Hs00559914_m1”“Hs00992679_m1” 40-7 “Hs00387770_m1” “Hs01031740_m1” “Hs00356958_m1”“Hs00959010_m1” “Hs01395177_m1” “Hs00705626_s1” “Hs01010736_m1”“Hs00703025_s1” “Hs00801390_s1” “Hs01894962_s1” “Hs00233987_m1”“Hs00174029_m1” “Hs00196245_m1” “Hs01051445_g1” “Hs00153408_m1”“Hs01081598_m1” “Hs00411188_g1” “Hs01089557_s1” “Hs01920599_gH”“Hs00901350_g1” “Hs00950371_m1” “Hs00997579_m1” “Hs00415546_m1”“Hs00884853_s1” “Hs00155241_m1” “Hs00915710_m1” “Hs03302824_pri”“Hs01025572_m1” “Hs00698959_m1” “Hs00167524_m1” “Hs00936519_m1”“Hs00992679_m1” “Hs00704853_s1” “Hs00960591_m1” “Hs00968305_m1”“Hs00380101_m1” “Hs00745492_s1” “Hs00201707_m1” “Hs00996236_m1”“Hs00366766_m1” 40-8 “Hs00155241_m1” “Hs01025572_m1” “Hs01087946_g1”“Hs00204257_m1” “Hs01395177_m1” “Hs05052601_s1” “Hs00962398_m1”“Hs03028557_s1” “Hs05033260_s1” “Hs00610058_m1” “Hs00174029_m1”“Hs05036222_s1” “Hs04189864_m1” “Hs00543973_m1” “Hs01081598_m1”“Hs01894962_s1” “Hs00738791_g1” “Hs00171042_m1” “Hs00957562_m1”“Hs01560931_m1” “Hs00231709_m1” “Hs01098278_m1” “Hs00703025_s1”“Hs01089557_s1” “Hs00374264_g1” “Hs01010736_m1” “Hs00901350_g1”“Hs00174969_m1” “Hs00260480_m1” “Hs00996236_m1” “Hs05016463_s1”“Hs00415546_m1” “Hs00362096_m1” “Hs00704853_s1” “Hs00975850_m1”“Hs00174705_m1” “Hs00251883_m1” “Hs00196245_m1” “Hs00222415_m1”“Hs01931732_s1” 40-9 “Hs00267207_m1” “Hs00904817_m1” “Hs01087946_g1”“Hs00233987_m1” “Hs04194422_s1” “Hs00196245_m1” “Hs03302824_pri”“Hs01089557_s1” “Hs00936519_m1” “Hs01560931_m1” “Hs00559914_m1”“Hs00171157_m1” “Hs00900510_m1” “Hs00174705_m1” “Hs00856927_g1”“Hs00950371_m1” “Hs01043717_m1” “Hs00960591_m1” “Hs01546752_g1”“Hs00957562_m1” “Hs00372831_g1” “Hs01029174_m1” “Hs00937509_m1”“Hs00411188_g1” “Hs05016463_s1” “Hs00705626_s1” “Hs00232157_m1”“Hs00174029_m1” “Hs00978280_m1” “Hs05052601_s1” “Hs05033260_s1”“Hs01920599_gH” “Hs00231709_m1” “Hs01098278_m1” “Hs01081598_m1”“Hs00997579_m1” “Hs01051445_g1” “Hs04232205_s1” “Hs00884853_s1”“Hs00738791_g1” 40-10 “Hs01076090_m1” “Hs00387770_m1” “Hs01031740_m1”“Hs00196245_m1” “Hs03464469_s1” “Hs04232205_s1” “Hs00884853_s1”“Hs00174969_m1” “Hs00607978_s1” “Hs04942686_m1” “Hs00931763_m1”“Hs01098278_m1” “Hs00996236_m1” “Hs00960591_m1” “Hs01920599_gH”“Hs01546752_g1” “Hs00997579_m1” “Hs01087946_g1” “Hs01560931_m1”“Hs00950371_m1” “Hs01549976_m1” “Hs00747379_m1” “Hs01081598_m1”“Hs01691258_g1” “Hs00231709_m1” “Hs00399035_m1” “Hs00428732_m1”“Hs00543973_m1” “Hs00240906_m1” “Hs00372831_g1” “Hs00703025_s1”“Hs00171042_m1” “Hs01043717_m1” “Hs01025572_m1” “Hs00222415_m1”“Hs00937509_m1” “Hs00267207_m1” “Hs00915710_m1” “Hs00366766_m1”“Hs00610058_m1” 40-11 “Hs00610058_m1” “Hs00745492_s1” “Hs00901350_g1”“Hs01051611_gH” “Hs01087946_g1” “Hs05052601_s1” “Hs03028557_s1”“Hs00248075_m1” “Hs01089557_s1” “Hs00738791_g1” “Hs00374264_g1”“Hs00543973_m1” “Hs04189864_m1” “Hs00698959_m1” “Hs05036222_s1”“Hs00962398_m1” “Hs00362096_m1” “Hs03043789_g1” “Hs03302824_pri”“Hs00380101_m1” “Hs00232157_m1” “Hs01553775_g1” “Hs01547054_m1”“Hs00174705_m1” “Hs00936519_m1” “Hs00386692_m1” “Hs00926053_m1”“Hs00996236_m1” “Hs00960591_m1” “Hs01098278_m1” “Hs01560931_m1”“Hs00202752_m1” “Hs04942686_m1” “Hs00428732_m1” “Hs01072228_m1”“Hs00884853_s1” “Hs00931763_m1” “Hs00964384_g1” “Hs00826827_g1”“Hs00155241_m1” 40-12 “Hs00174705_m1” “Hs00698959_m1” “Hs01546752_g1”“Hs00262107_m1” “Hs03464469_s1” “Hs00996236_m1” “Hs00960591_m1”“Hs00387770_m1” “Hs00204257_m1” “Hs00801390_s1” “Hs00610058_m1”“Hs01631495_s1” “Hs01081598_m1” “Hs00240906_m1” “Hs01553775_g1”“Hs00362096_m1” “Hs00899658_m1” “Hs00248075_m1” “Hs01894962_s1”“Hs01089557_s1” “Hs00747379_m1” “Hs01560931_m1” “Hs00267207_m1”“Hs01010736_m1” “Hs00901350_g1” “Hs03302824_pri” “Hs01547054_m1”“Hs00386692_m1” “Hs01098278_m1” “Hs00399035_m1” “Hs00189880_m1”“Hs00232157_m1” “Hs00356958_m1” “Hs00167524_m1” “Hs00380101_m1”“Hs04942686_m1” “Hs00174969_m1” “Hs00968305_m1” “Hs00745492_s1”“Hs00366766_m1” 40-13 “Hs01546752_g1” “Hs01920599_gH” “Hs00801390_s1”“Hs01560931_m1” “Hs04194422_s1” “Hs01081598_m1” “Hs00251883_m1”“Hs00559914_m1” “Hs00262107_m1” “Hs00374264_g1” “Hs00543973_m1”“Hs00171157_m1” “Hs00937509_m1” “Hs01029174_m1” “Hs00174969_m1”“Hs00232157_m1” “Hs00705626_s1” “Hs05016463_s1” “Hs01553775_g1”“Hs00704853_s1” “Hs01691258_g1” “Hs00167524_m1” “Hs00962398_m1”“Hs00978280_m1” “Hs00248075_m1” “Hs00386692_m1” “Hs00959010_m1”“Hs01098278_m1” “Hs00884853_s1” “Hs00174705_m1” “Hs00996236_m1”“Hs00379134_m1” “Hs04942686_m1” “Hs00202752_m1” “Hs00189880_m1”“Hs00365956_m1” “Hs03302824_pri” “Hs00926053_m1” “Hs01395177_m1”“Hs04189864_m1” 40-14 “Hs00747379_m1” “Hs00362096_m1” “Hs00386692_m1”“Hs01089557_s1” “Hs01029174_m1” “Hs00960591_m1” “Hs00248075_m1”“Hs01547054_m1” “Hs01631495_s1” “Hs00189880_m1” “Hs00167524_m1”“Hs01098278_m1” “Hs00996236_m1” “Hs00240906_m1” “Hs01087946_g1”“Hs00884853_s1” “Hs00899658_m1” “Hs00380101_m1” “Hs04942686_m1”“Hs00936519_m1” “Hs00856927_g1” “Hs01043717_m1” “Hs00915710_m1”“Hs00231709_m1” “Hs00964384_g1” “Hs00387770_m1” “Hs00155241_m1”“Hs01081598_m1” “Hs00926053_m1” “Hs00366766_m1” “Hs00171042_m1”“Hs01031740_m1” “Hs00959010_m1” “Hs01546752_g1” “Hs00233987_m1”“Hs01042796_m1” “Hs00896999_g1” “Hs00374264_g1” “Hs04232205_s1”“Hs00201707_m1” 40-15 “Hs00703025_s1” “Hs01087946_g1” “Hs05016463_s1”“Hs00167524_m1” “Hs00543973_m1” “Hs01010736_m1” “Hs05052601_s1”“Hs00957562_m1” “Hs00856927_g1” “Hs04232205_s1” “Hs01029174_m1”“Hs00251883_m1” “Hs01931732_s1” “Hs00262107_m1” “Hs00374264_g1”“Hs01560931_m1” “Hs00174969_m1” “Hs00937509_m1” “Hs00222415_m1”“Hs00801390_s1” “Hs00959010_m1” “Hs00231709_m1” “Hs00747379_m1”“Hs00411188_g1” “Hs01051445_g1” “Hs00174029_m1” “Hs01553775_g1”“Hs01072228_m1” “Hs01089557_s1” “Hs00415546_m1” “Hs00705626_s1”“Hs00387770_m1” “Hs00745492_s1” “Hs00153408_m1” “Hs00196245_m1”“Hs00884853_s1” “Hs04189864_m1” “Hs00936519_m1” “Hs00958111_m1”“Hs00607978_s1” 40-16 “Hs01920599_gH” “Hs04189864_m1” “Hs01114274_m1”“Hs01395177_m1” “Hs00374264_g1” “Hs00174029_m1” “Hs00958111_m1”“Hs03028557_s1” “Hs00856927_g1” “Hs00153408_m1” “Hs01089557_s1”“Hs00607978_s1” “Hs00201707_m1” “Hs00155241_m1” “Hs00233987_m1”“Hs00745492_s1” “Hs00610058_m1” “Hs00964384_g1” “Hs04942686_m1”“Hs00996236_m1” “Hs00174969_m1” “Hs00944507_g1” “Hs00248075_m1”“Hs00362096_m1” “Hs00174705_m1” “Hs01043717_m1” “Hs00260452_m1”“Hs00167524_m1” “Hs00380101_m1” “Hs00559914_m1” “Hs00159178_m1”“Hs04194422_s1” “Hs00399035_m1” “Hs01931732_s1” “Hs00703025_s1”“Hs00738791_g1” “Hs00826827_g1” “Hs00997579_m1” “Hs00204257_m1”“Hs01070154_m1” 40-17 “Hs00978280_m1” “Hs01553775_g1” “Hs01029174_m1”“Hs00996236_m1” “Hs00386692_m1” “Hs00738791_g1” “Hs01089557_s1”“Hs00365956_m1” “Hs00607978_s1” “Hs00248075_m1” “Hs01098278_m1”“Hs00962398_m1” “Hs00196245_m1” “Hs00232157_m1” “Hs00167524_m1”“Hs04942686_m1” “Hs00201707_m1” “Hs00915710_m1” “Hs01549976_m1”“Hs00901350_g1” “Hs04194422_s1” “Hs00997579_m1” “Hs01031740_m1”“Hs00904817_m1” “Hs01631495_s1” “Hs00153408_m1” “Hs00975850_m1”“Hs00428732_m1” “Hs00366766_m1” “Hs04232205_s1” “Hs01547054_m1”“Hs00900510_m1” “Hs01560931_m1” “Hs00747379_m1” “Hs00356958_m1”“Hs00899658_m1” “Hs00415546_m1” “Hs00362096_m1” “Hs00937509_m1”“Hs00958111_m1” 40-18 “Hs00201707_m1” “Hs04942686_m1” “Hs04194422_s1”“Hs00899658_m1” “Hs00260452_m1” “Hs01043717_m1” “Hs00262107_m1”“Hs01070154_m1” “Hs01029174_m1” “Hs00856927_g1” “Hs01098278_m1”“Hs00996236_m1” “Hs00944507_g1” “Hs00372831_g1” “Hs00356958_m1”“Hs01051611_gH” “Hs00380101_m1” “Hs01076090_m1” “Hs00703025_s1”“Hs00251883_m1” “Hs01560931_m1” “Hs00171157_m1” “Hs00386692_m1”“Hs05016463_s1” “Hs00167524_m1” “Hs01089557_s1” “Hs00171042_m1”“Hs00745492_s1” “Hs00610058_m1” “Hs00884853_s1” “Hs00958111_m1”“Hs04189864_m1” “Hs00704853_s1” “Hs00543973_m1” “Hs00374264_g1”“Hs01087946_g1” “Hs00415546_m1” “Hs05036222_s1” “Hs00904817_m1”“Hs01072228_m1” 40-19 “Hs01072228_m1” “Hs00915710_m1” “Hs00174705_m1”“Hs00356958_m1” “Hs00174029_m1” “Hs00958111_m1” “Hs00248075_m1”“Hs01553775_g1” “Hs01098278_m1” “Hs00957562_m1” “Hs00937509_m1”“Hs00960591_m1” “Hs00747379_m1” “Hs00387770_m1” “Hs01547054_m1”“Hs00698959_m1” “Hs00399035_m1” “Hs00607978_s1” “Hs04942686_m1”“Hs00240906_m1” “Hs00962398_m1” “Hs00232157_m1” “Hs00267207_m1”“Hs00996236_m1” “Hs00704853_s1” “Hs00365956_m1” “Hs00196245_m1”“Hs00959010_m1” “Hs00884853_s1” “Hs01691258_g1” “Hs00950371_m1”“Hs00260480_m1” “Hs00174969_m1” “Hs01560931_m1” “Hs00964384_g1”“Hs00738791_g1” “Hs00543973_m1” “Hs00171042_m1” “Hs04189864_m1”“Hs00415546_m1” 40-20 “Hs00559914_m1” “Hs00856927_g1” “Hs00232157_m1”“Hs01029174_m1” “Hs00978280_m1” “Hs01051445_g1” “Hs01031740_m1”“Hs00899658_m1” “Hs00174705_m1” “Hs00153408_m1” “Hs00362096_m1”“Hs00944507_g1” “Hs00260452_m1” “Hs00937509_m1” “Hs00826827_g1”“Hs00248075_m1” “Hs01043717_m1” “Hs01070154_m1” “Hs01076090_m1”“Hs01560931_m1” “Hs01920599_gH” “Hs00543973_m1” “Hs00380101_m1”“Hs00997579_m1” “Hs03043789_g1” “Hs00901350_g1” “Hs03302824_pri”“Hs00399035_m1” “Hs00747379_m1” “Hs01114274_m1” “Hs04232205_s1”“Hs05016463_s1” “Hs00387770_m1” “Hs00366766_m1” “Hs04194422_s1”“Hs01008033_m1” “Hs01395177_m1” “Hs00904817_m1” “Hs03464469_s1”“Hs01894962_s1” 40-21 “Hs00826827_g1” “Hs00899658_m1” “Hs01076090_m1”“Hs00411188_g1” “Hs05036222_s1” “Hs00171042_m1” “Hs00926053_m1”“Hs00233987_m1” “Hs00174029_m1” “Hs00902334_m1” “Hs00958111_m1”“Hs00153408_m1” “Hs01081598_m1” “Hs01051445_g1” “Hs04189864_m1”“Hs00962398_m1” “Hs00155241_m1” “Hs00380101_m1” “Hs01560931_m1”“Hs00167524_m1” “Hs00171157_m1” “Hs00260480_m1” “Hs00174969_m1”“Hs01114274_m1” “Hs00705626_s1” “Hs01920599_gH” “Hs00428732_m1”“Hs01031740_m1” “Hs05016463_s1” “Hs01549976_m1” “Hs00931763_m1”“Hs00703025_s1” “Hs00960591_m1” “Hs05052601_s1” “Hs00937509_m1”“Hs01098278_m1” “Hs00968305_m1” “Hs01087946_g1” “Hs00959010_m1”“Hs01089557_s1” 40-22 “Hs00904817_m1” “Hs00260480_m1” “Hs00856927_g1”“Hs01894962_s1” “Hs00171042_m1” “Hs00171157_m1” “Hs01098278_m1”“Hs00202752_m1” “Hs01076090_m1” “Hs00964384_g1” “Hs00155241_m1”“Hs00950371_m1” “Hs01042796_m1” “Hs00826827_g1” “Hs00958111_m1”“Hs00899658_m1” “Hs00233987_m1” “Hs00926053_m1” “Hs01029174_m1”“Hs00174029_m1” “Hs01081598_m1” “Hs00159178_m1” “Hs00975850_m1”“Hs00232157_m1” “Hs00251883_m1” “Hs00372831_g1” “Hs00957562_m1”“Hs00610058_m1” “Hs01043717_m1” “Hs05033260_s1” “Hs01920599_gH”“Hs00543973_m1” “Hs01560931_m1” “Hs00901350_g1” “Hs00705626_s1”“Hs05016463_s1” “Hs00260452_m1” “Hs01553775_g1” “Hs00153408_m1”“Hs00962398_m1” 40-23 “Hs00801390_s1” “Hs00174969_m1” “Hs00959010_m1”“Hs00968305_m1” “Hs01547054_m1” “Hs01072228_m1” “Hs00262107_m1”“Hs01114274_m1” “Hs00937509_m1” “Hs01051611_gH” “Hs01920599_gH”“Hs01031740_m1” “Hs00399035_m1” “Hs00962398_m1” “Hs00233987_m1”“Hs00167524_m1” “Hs00826827_g1” “Hs01010736_m1” “Hs03302824_pri”“Hs01549976_m1” “Hs00901350_g1” “Hs00975850_m1” “Hs00904817_m1”“Hs00380101_m1” “Hs00387770_m1” “Hs04232205_s1” “Hs00240906_m1”“Hs00997579_m1” “Hs01560931_m1” “Hs01631495_s1” “Hs05052601_s1”“Hs00738791_g1” “Hs00171157_m1” “Hs00232157_m1” “Hs00978280_m1”“Hs00372831_g1” “Hs00704853_s1” “Hs00745492_s1” “Hs00936519_m1”“Hs00204257_m1” 40-24 “Hs01549976_m1” “Hs00260480_m1” “Hs01031740_m1”“Hs05052601_s1” “Hs05016463_s1” “Hs00196245_m1” “Hs01025572_m1”“Hs01042796_m1” “Hs00944507_g1” “Hs00171157_m1” “Hs00167524_m1”“Hs00962398_m1” “Hs00428732_m1” “Hs00543973_m1” “Hs01560931_m1”“Hs01087946_g1” “Hs00960591_m1” “Hs04189864_m1” “Hs00826827_g1”“Hs00380101_m1” “Hs01691258_g1” “Hs00386692_m1” “Hs00374264_g1”“Hs00745492_s1” “Hs00884853_s1” “Hs00411188_g1” “Hs00936519_m1”“Hs00240906_m1” “Hs00232157_m1” “Hs01098278_m1” “Hs03302824_pri”“Hs00248075_m1” “Hs00801390_s1” “Hs01553775_g1” “Hs03464469_s1”“Hs00738791_g1” “Hs01631495_s1” “Hs00703025_s1” “Hs00896999_g1”“Hs01010736_m1” 40-25 “Hs04189864_m1” “Hs00386692_m1” “Hs00926053_m1”“Hs00260452_m1” “Hs00610058_m1” “Hs00958111_m1” “Hs00704853_s1”“Hs00380101_m1” “Hs00543973_m1” “Hs00167524_m1” “Hs00747379_m1”“Hs00428732_m1” “Hs00559914_m1” “Hs00738791_g1” “Hs00260480_m1”“Hs00703025_s1” “Hs00975850_m1” “Hs01025572_m1” “Hs01098278_m1”“Hs01560931_m1” “Hs00745492_s1” “Hs00233987_m1” “Hs00232157_m1”“Hs05016463_s1” “Hs00607978_s1” “Hs00171042_m1” “Hs00884853_s1”“Hs01691258_g1” “Hs00196245_m1” “Hs01081598_m1” “Hs00251883_m1”“Hs00904817_m1” “Hs01114274_m1” “Hs00222415_m1” “Hs01051445_g1”“Hs01042796_m1” “Hs00356958_m1” “Hs00944507_g1” “Hs00379134_m1”“Hs00705626_s1” See Table 11 for gene name associated with each probeID.

Example 6: 40-GEP to Predict Metastatic Risk in Cutaneous SCC StudyDesign—Development and Validation

To develop and validate a gene expression signature capable ofstratifying patient risk of regional or distant metastasis, aprospectively-designed biomarker study was conducted on archival primarySCC formalin-fixed paraffin-embedded (FFPE) tissue (FIG. 5). The primaryend point for this study was metastasis-free survival (MFS), includingboth regional and distant metastatic events. Regional metastasis wasdefined as a metastatic lesion within the regional nodal basin,including satellite or in-transit metastasis, but excluding localrecurrence. Distant metastasis was defined as metastasis beyond theregional lymph node basin. Disease-specific death, a secondary endpoint, was defined as death from SCC documented in patient medicalrecords.

Expression of 140 candidate genes was determined for all samples in thediscovery and development cases (cohort 1, n=202). Deep learning wasapplied to expression data from 122 genes passing initial expressionthresholds to select genes for further signature training. Theprognostic algorithm encompassing the 40-GEP assay was selected based onperformance in training and gene coefficients were locked prior tovalidation. Power calculations indicated that the validation cohort(cohort 2, n=321) could detect a hazard ratio of 2.1 for metastasis with90% power, alpha=0.05. After validation of the algorithm using cohort 2,clinically-actionable cut-points for probability scores from the modelswere set to optimize negative predictive value (NPV), positivepredictive value (PPV), and sensitivity for metastasis-risk groups(Class 1: low risk; Class 2A: high/moderate risk; Class 2B: highestrisk).

Detailed Study Design—Discovery and Development

For model training (cohort 1, training set), probes were filtered basedon the consistency of expression across preliminary runs across 140probes. The initial set of probes was filtered for amplification andstability of gene expression, resulting in 122 discriminant probes and 6control probes (MDM2 (Hs00540450_s1), KMT2D (Hs00912419_m1), BAG6(Hs00190383_m1), FXR1 (Hs01096876_g1), MDM4 (Hs00967238_m1), and KMT2C(Hs01005521_m1). Cases were filtered based on detectable expression ofat least 90% of the candidate discriminant probes. Deep learningtechniques were applied to gene expression data from cohort 1 for geneselection and model identification. To ensure proper classification, thetraining set was restricted to cases with a documented metastatic eventor at least 4 years of follow up. Gene expression using 140 candidateprobes identified by literature review or through preliminary discoveryefforts was determined for all samples in cohort 1. Triplicate geneexpression data were aggregated and normalized using the control probesidentified from the larger case set. Genetic algorithms combined withneural network models were used to generate two independent predictionalgorithms from the 122 cases and 122 predictive probes passing initialexpression thresholds. Genetic algorithms optimized neural networkpredictive algorithms across a range of target gene set sizes. Initialmodels were generated by training neural network models to a set of 100randomly generated gene lists from the set of 122 without replacement.At each iteration of the genetic algorithm, the top 25% of models wereretained and their gene lists mated by randomly selecting approximately45% of the genes from each list, removing duplicates, and then fillingthe list to the target size by selecting genes from the remaining 122gene set. This process provided a minimum 10% mutation rate at eachiteration. Genetic improvement continued until the mean kappa value forthe population improved by less than 0.01. Neural networkhyperparameters were optimized using a training control of 10 times4-fold repeated cross validation with hyperparameter selection based onthe maximum kappa value. The final model was trained against alltraining data using the optimal hyperparameter set. Two models weredeveloped, one using no weighting, and another weighting metastasis astwice that of nonmetastasis, which together generated the lockedalgorithm for the 40-GEP test.

Patient Enrollment, Specimen Acquisition, and Cohort Definitions

Archived FFPE primary cutaneous SCC tissue and associated de-identifiedclinical data were obtained from 23 independent centers followingInstitutional Review Board (IRB) approval. Associated clinical,pathological, and outcomes data were entered onto a secure case reportform (CRF) and on-site data monitoring was performed for all cases. Aspart of the ongoing study protocol, 586 archival SCC cases with completeCRFs and FFPE tissue were received. The workflow diagram in FIG. 5summarizes protocol inclusion/exclusion criteria. Briefly, inclusioncriteria specified pathologically confirmed cutaneous SCC with availableFFPE tissue from either the original biopsy or the definitive surgicalexcision. Subjects had a documented regional or distant metastasis, or aminimum of three years of clinical follow-up without evidence ofmetastasis. The protocol targeted enrollment of cases for theintent-to-treat patient population. The protocol targeted enrollment ofwith at least one high-risk feature as defined by guidelines or stagingsystems (features considered high-risk for targeted enrollment include,but are not limited to, any single clinicopathological feature by whicha patient could be deemed NCCN-high risk or increase a patient's T-stageabove T1), either at the patient or tumor level, to best model theintent-to-treat patient population. Centralized pathology review of arepresentative hematoxylin and eosin (H&E) stained tissue section wasperformed by a board-certified dermatopathologist to confirm diagnosisof SCC and assess for high-risk features. Per study design, the first˜200 cases received and monitored were selected for discovery anddevelopment (cohort 1 n=202) and the remaining cases for validation(cohort 2 n=324).

All CRFs were monitored, which included review of all availablepathology reports and medical records associated with received lesions.For cohort 2, monitors reviewed 98.4% (314/319) of all pathology reportsfrom definitive surgeries. Two cases did not receive definitive surgery.All cases were categorized as NCCN low or high risk and were restaged byAJCC 8th Edition and BWH criteria per features listed in the originalpathology reports, available medical records, and independentdermatopathologist review. Consistent with College of American Pathology(CAP) reporting protocols, histopathological features not reported ornot identified were considered negative for staging and analysis.

Assay Methods

FFPE tissue sections were freshly cut to 5 μm sections at thecontributing institution and collected at a central CAP-accreditedlaboratory. Tumor tissue was macrodissected from slides, including tumorstroma and infiltrating immune cells, and processed to generate RNA andcDNA.

Each cDNA sample underwent a 14-cycle preamplification step prior todilution, and then was mixed 1:1 with 2× TaqMan Gene Expression MasterMix. Quantitative polymerase chain reaction (qPCR) was then performedusing high-throughput microfluidics gene cards containing primersspecific to the genes of interest and the QuantStudio 12K Flex Real-TimePCR System (Life Technologies). Each sample was run in triplicate withsamples randomized onto plates to distribute metastatic andnonmetastatic cases. Laboratory personnel and clinical monitoring staffwere blinded to GEP results during data capture.

Statistical Analysis

Survival analyses using the Kaplan-Meier method were performed in R(version 2.44) with survival statistics calculated using either thelog-rank test or multivariate Cox regression analysis when appropriate.For Cox regression, analysis assumptions of proportional hazards wereconfirmed using the zph test of the fitted model. In cases whereproportional hazards assumptions were violated in Cox regression models,additional multivariate survival regression models were used to confirmthe results. Binned 40-GEP results and risk according to establishedstaging methods were included in regression models. Accuracy metricswere assessed for GEP Classes, both Class 2A and 2B as the high-riskgroup for completeness, and clinical risk staging parameters usingfunctions in the caret package (version 6.0) in R (version 3.6.1).

Results Development of the Prognostic Signature

To identify a prognostic signature capable of patient stratification byrisk of regional or distant metastasis from primary SCC tumors, deeplearning was applied to gene expression data from training cohort(n=122, 13 metastatic cases). Demographics of the training cohort areshown in FIG. 12. The algorithm selected for validation was comprised oftwo gene expression signatures, inclusive of 6 control and 34discriminant genes in total, with risk modeling performed using neuralnetworks. This 40-GEP algorithm generated linear scores for probabilityof metastasis from each predictive signature.

Independent Validation Cohort Demographics

The validation cohort of 321 primary SCC cases was comprised of 52 cases(16%) with documented metastasis, and 269 cases without a metastaticevent. Baseline cohort characteristics are summarized in FIG. 7. Most ofthe patients were Caucasian (99.7%), non-Hispanic (97.2%), male (73.2%),and immunocompetent (76.3%) with tumors located on the head and neck(66.7%), consistent with typical SCC presentation. According to NCCNGuidelines® criteria, 93% were high risk. The surgical treatmentmodalities were Mohs surgery (79.8%) and wide local excision (19.6%).The following clinicopathologic features were statistically differentbetween metastatic and nonmetastatic cases in univariate analysis: tumordifferentiation, perineural invasion, invasion into subcutaneous fat,tumor thickness, tumor diameter, lymphovascular invasion, tumor locatedon head/neck, definitive surgery as Mohs micrographic surgery, Clarklevel, and patient sex.

Independent Validation of the 40-GEP Prognostic Signature

To validate the prognostic capability of the 40-GEP, the algorithm wasapplied to independent cohort 2. The algorithm demonstrated astatistically significant ability to stratify metastatic risk. Thevalidated 40-GEP was then used to define risk groups with increasingmetastasis risk: Class 1 (low risk, n=203), Class 2A (high risk, n=93),and Class 2B (highest risk, n=25). Significantly different 3-year MFSrates were observed for Class 1 (91.6%), Class 2A (80.6%), and Class 2B(44.0%) groups following Kaplan-Meier survival analysis (FIG. 6,log-rank test, p<0.0001). The overall rates of metastasis in each Classwere 8.9%, 20.4%, and 60.0%, respectively. The final gene signatureidentified 64% (34 of 52) of the cases having metastasis as Class 2,with 15 cases identified as Class 2B. The 40-GEP Class was associatedwith disease-specific death resulting in a hazard ratio of 5.4 and 8.8for Class 2A and Class 2B, respectively (univariate model; p<0.05,p<0.01). Of the 13 reported deaths due to SCC, 10 were classified asClass 2 (7 Class 2A and 3 Class 2B).

Prognostic Accuracy of the 40-GEP Test Compared to Staging Systems

The 40-GEP signature was an independent predictor of risk when analyzedin a multivariate model with AJCC (Class 2A HR=2.17, p=0.019; Class 2BHR=9.34, p<0.0001) or BWH (Class 2A HR=2.23, p=0.016; Class 2B HR=8.68,p<0.0001) staging systems (see FIG. 8 and FIG. 11). Multivariateanalysis with individual clinicopathological features also demonstratesthat the 40-GEP signature demonstrates independent prognostic value overthese features (see FIG. 13). FIG. 9 reports the number of cases with orwithout metastasis in the validation cohort according to 40-GEP Classand with respect to NCCN risk group or T-stage.

Overall, accuracy metrics for AJCC (T1/T2 vs. T3/T4) and BWH staging(T1/T2a vs. T2b/T3) align with previously published data (FIG. 10; seeRuiz et al., JAMA Dermatol. 155: 819 (2019); Karia et al., JAMADermatol. 154: 175 (2018); Jambusaria-Pahlajani et al., JAMA Dermatol.149: 402 (2013); and Karia et al., KO 32: 327-334 (2014)). The 40-GEPClass 2B group demonstrated a PPV of 60% compared to 16.7%, 22.0%, and35.6% for NCCN, AJCC, and BWH high-risk groups, respectively (see FIG.10). The Class 1 group was associated with a 91.1% NPV, exceeding the87.6% and 87.0% NPV for AJCC and BWH staging, respectively, and matchingthe 90.5% NPV of NCCN. Importantly, 63% of the validation cohort overalland 67% of the high-risk NCCN cases were identified as low risk Class 1by the 40-GEP with the highest NPV relative to NCCN, AJCC, and BWH.

TABLE 14 Discriminant genes (n = 34) included in the prognosticsignature. GENE ID GENE NAME ACSBG1 Long-chain-fatty-acid--CoA ligaseACSBG1 ALOX12 Arachidonate 12-Lipoxygenase, 12S Type APOBEC3GApolipoprotein B MRNA Editing Enzyme Catalytic Subunit 3G ATP6V0E2ATPase H+ Transporting V0 Subunit E2 BBC3 Bcl-2-binding component 3BHLHB9 Basic Helix-Loop-Helix Family Member B9 CEP76 Centrosomal proteinof 76 kDa DUXAP8 Double Homeobox A Pseudogene 8 GTPBP2 GTP BindingProtein 2 HDDC3 Guanosine-3′,5′-bis(diphosphate) 3′-pyrophosphohydrolaseMESH1 ID2 Inhibitor Of DNA Binding 2 LCE2B Late Cornified Envelope 2BLIME1 (ZGPAT) Lck Interacting Transmembrane Adaptor 1 LOC100287896Uncharacterized LOC100287896 LOC101927502 Uncharacterized LOC101927502MMP10 Matrix Metalloproteinase 10 (Stromelysin 2) MRC1 Mannose ReceptorC-Type 1 MSANTD4 Myb/SANT DNA Binding Domain Containing 4 WithCoiled-Coils NFASC Neurofascin NFIC Nuclear Factor I C PDPN PodoplaninPI3 Peptidase Inhibitor 3 PLS3 Plastin 3 RCHY1 Ring Finger And CHY ZincFinger Domain Containing 1 RNF135 Ring Finger Protein 135 RPP38Ribonuclease P/MRP Subunit P38 RUNX3 Runt-Related Transcription Factor 3SLC1A3 Solute Carrier Family 1 Member 3 SPP1 Osteopontin TAF6L TATA-BoxBinding Protein Associated Factor 6 Like TFAP2B Transcription FactorAP-2 Beta ZNF48 Zinc Finger Protein 48 ZNF496 Zinc Finger Protein 496ZNF839 Zinc Finger Protein 839

TABLE 15 34 discriminant genes included in GEP gene set able to predictrisk of recurrence and/or metastasis Change in gene expression inrecurrent cancer when Probe Identifier compared to non-recurrent Genename (ThermoFisher) cancer. ACSBG1 Hs01025572_m1 decrease ALOX12Hs00167524_m1 decrease APOBEC3G Hs00222415_m1 increase ATP6V0E2Hs04189864_m1 increase BBC3 Hs00248075_m1 increase BHLHB9 Hs01089557_s1decrease CEP76 Hs00950371_m1 decrease DUXAP8 Hs04942686_m1 increaseGTPBP2 Hs01051445_g1 decrease HDDC3 Hs00826827_g1 increase ID2Hs00747379_m1 decrease LCE2B Hs04194422_s1 decrease LIME1 (ZGPAT)Hs00738791_g1 increase LOC101927502 Hs05033260_s1 increase LOC100287896Hs01931732_s1 increase MMP10 Hs00233987_m1 decrease MRC1 Hs00267207_m1decrease MSANTD4 Hs00411188_g1 decrease NFASC Hs00978280_m1 decreaseNFIC Hs00232157_m1 decrease PDPN Hs00366766_m1 decrease PI3Hs00964384_g1 decrease PLS3 Hs00543973_m1 decrease RCHY1 Hs00996236_m1increase RNF135 Hs00260480_m1 increase RPP38 Hs00705626_s1 decreaseRUNX3 Hs00231709_m1 increase SLC1A3 Hs00904817_m1 increase SPP1Hs00959010_m1 increase TAF6L Hs01008033_m1 increase TFAP2B Hs01560931_m1decrease ZNF48 Hs00399035_m1 increase ZNF496 Hs00262107_m1 increaseZNF839 Hs00901350_g1 increase Control genes: MDM2 (Hs00540450_s1), KMT2D(Hs00912419_m1), BAG6 (Hs00190383_m1), FXR1 (Hs01096876_g1), MDM4(Hs00967238_m1), and KMT2C (Hs01005521_m1).

Example 7: Integrating Gene Expression Profiling into NCCN High-RiskCutaneous Squamous Cell Carcinoma Management Recommendations: Impact onPatient Management and Outcomes

Cutaneous squamous cell carcinoma (cSCC) is the second most common formof skin cancer after basal cell carcinoma. It occurs in approximatelyone million people in the U.S. and the incidence is rising, partly dueto enhanced detection methods and an aging population. Overall,approximately 6% of cSCC patients develop regional or distant metastaticlesions and survival rates are low for those who do develop metastasis.The number of deaths from cSCC, a large proportion of which are precededby metastasis, has been estimated to rival that from melanoma.Therefore, accurate prediction of risk for metastasis is essential foroptimal patient management and improving outcomes.

National Comprehensive Cancer Network (NCCN) Guidelines® outline broadapproaches for management of cSCC patients considered high risk fordeveloping recurrence and/or metastasis. Risk stratification and stagingsystems for cSCC include NCCN Guidelines Criteria®, the American JointCommittee on Cancer (AJCC) Cancer Staging Manual (8th Edition), and theBrigham and Women's Hospital (BWH) tumor classification system. Thesesystems are based on clinical and pathological features; however, theyare specifically limited in their ability to predict adverse outcomes(i.e., have low positive predictive value (PPV) for metastasis) and posea challenge to implementing risk-directed patient management. Patientswith cSCC would benefit from improved prognostic tools for determiningwhich patients currently considered clinicopathologically “high risk”are truly at low risk, which patients should consider procedures todetect nodal/distant disease (e.g., node biopsy versus imaging versusclinical examination only), and which should consider therapeuticintervention to reduce risk for recurrence/metastasis (e.g., adjuvantradiation, chemotherapy, additional surgery, and clinical trialenrollment). Given that risk classifications guide treatment plans,improved prognostic tools would enhance shared decision-making betweenphysicians and their patients. Ultimately, the goal is earlyintervention for individuals who are likely to develop metastasis andavoidance of unnecessary invasive or costly procedures for those who areat lower risk for developing metastasis.

The 40-gene expression profile (40-GEP) test using archival,formalin-fixed paraffin-embedded (FFPE), primary cSCC tissue asdisclosed herein stratifies clinicopathologically identified high-riskcSCC tumors into three risk groups based on low (Class 1), high (Class2A), and highest (Class 2B) risk for regional or distant metastasis at 3years after diagnosis. A substantially higher PPV (60.0%) was found forthe 40-GEP test for Class 2B relative to that found for the AJCC (22.0%)and BWH (35.6%) staging systems, while maintaining a negative predictivevalue (NPV) of approximately 90.0% (which is similar to that of the AJCCand BWH systems). The primary goal of developing and validating the40-GEP test was to improve metastasis risk prediction.

Applying the 40-GEP test to risk-directed management recommendationsfrom the NCCN Guidelines® for 300 NCCN-defined high-risk cSCC cases ofthe 40-GEP clinical validation cohort demonstrated that integration of amolecular prognostic tool with higher PPV, and similar NPV, relative tocurrent staging systems can identify a subgroup (40-GEP Class 1 andlow-risk T stage) of NCCN-defined high-risk patients with rates ofmetastasis similar to those in the clinicopathologic low-risk group,suggesting this subgroup could be managed less aggressively. Bycomparison, integration of the 40-GEP test also suggested that a patientwith a Class 2B tumor with a high risk for metastasis would warrantintensified intervention, thereby achieving risk-appropriate allocationof surgical, imaging, and therapeutic resources. In all, integrating the40-GEP test into risk-directed guidelines for patient managementresulted in more personalized treatment recommendations and potentialimprovement of net health outcomes. This was accomplished by identifyingboth a low-risk subgroup (more than 50% of the cohort) that could bemanaged conservatively (low intensity management) and a smaller subgroup(8%) of patients who were at higher risk for metastasis and wouldrequire more aggressive intervention (high intensity management).

Materials and Methods

Integration of 40-GEP within High-Risk NCCN Patient ManagementGuidelines

For NCCN-defined high-risk patients from the 40-GEP clinical validationcohort, metastasis risk Class (40-GEP results), T stage, and knownpatient outcomes were extracted. This high-risk cohort (n=300) includedonly cases meeting study criteria and having one or more NCCN-definedhigh-risk feature, as noted in FIG. 16. Briefly, criteria for studyinclusion were pathologically-confirmed cSCC diagnosed after Jan. 1,2006; available archival, FFPE primary cSCC tumor tissue; complete casereport forms; and documented metastasis or minimum follow-up period of 3years without metastasis. Study cohort demographics and clinicalcharacteristics were monitored and underwent centralized pathologyreview (FIG. 16).

Data Analysis and Risk-Aligned Management Recommendations

For the NCCN high-risk cohort (n=300), the cases stratified in each40-GEP Class, along with corresponding metastasis rates and T stage,were analyzed to align each patient group (40-GEP Class/T stage) withrisk-appropriate management recommendations. Within the framework ofNCCN Guidelines® for management of high-risk cSCC patients withlocalized disease, risk-aligned management recommendations based on40-GEP results and T stage were developed for low, moderate, and highintensity management to correspond with metastasis risk bins of <10%,10-50%, and >50% risk, respectively. Risk-aligned managementrecommendations addressed follow-up, imaging, nodal assessment, adjuvanttherapy, and clinical trials.

Results Cohort Characteristics, 40-GEP Risk Classification, and Outcomes

A 300-case cohort of NCCN high-risk cSCC patients (FIG. 16) was used tointegrate a recently validated 40-GEP test into NCCN Guidelines® and Tstage criteria for patient management to develop risk-aligned managementrecommendations. The 40-GEP test classifies patients into three riskgroups: Class 1, Class 2A, and Class 2B, having low, high, and highestrisk for metastasis at 3 years post-diagnosis, respectively. Of the 300cases, 189 (63.0%) were Class 1, 87 (29.0%) were Class 2A, and 24 (8.0%)were Class 2B with overall metastasis rates of 9%, 21%, and 63%,respectively (see FIG. 14A). More than 50% of the cases were Class 1 andAJCC T1-T2 (n=159, 53.0%) or BWH T1-T2a (n=173, 57.7%) with metastasisrates below 10% (AJCC, 7.5%; BWH, 8.1%) (see FIGS. 14A and 14B).Whereas, Class 1 cases that were also AJCC T3-T4 or BWH T2b-T3, as wellas all Class 2A cases, had metastasis rates above 10%, but lower than50%. All Class 2B cases (8.0% of the cohort) had metastasis rates thatwere greater than 50%.

Clinical Utility of Integrating the 40-GEP Test

By combining the low-risk Class 1 result with AJCC T1-T2 stage, a 3-yearmetastasis rate of 7.5% (NPV, 92.5%) was identified for this subgroup(see FIGS. 14 and 15). This metastasis rate for this subgroup within theNCCN high-risk cohort is approaching the rate reported for the generalcSCC patient population (<6% metastasis). Of the Class 1 cases, 159 and173 were AJCC T1-T2 and BWH T1-T2a, respectively, and were risk-alignedfor receiving low intensity management (see FIGS. 14A and 14B). The40-GEP identified a highest-risk (Class 2B) subpopulation (n=24, 8.0%)which was risk-aligned for receiving high intensity management,consisting of 16 and 8 patients who were AJCC T1-T2 and T3-T4,respectively, and 17 and 7 who were BWH T1-2a and T2b-T3, respectively.Of the remainder of the cohort, 64 were Class 2A/AJCC T1-T2 and 73 wereClass 2A/BWH T1-T2a, with a risk for metastasis of 15.6% and 17.8%,respectively (FIG. 14A). These rates are lower than that for the overallcohort, but still more than twice that of the general cSCC patientpopulation. Moderate intensity management was suggested for this group,as well as those patients who were Class 1 or 2A and AJCC T3-T4 or BWHT2b-T3 (see FIGS. 14A and 14B).

The 40-GEP test results, when adjusted for AJCC or BWH T stage in thisstudy, suggest low management intensity for 53.0% or 57.7% of the300-patient cohort, respectively (FIG. 14). As shown in FIG. 15, lowintensity management for these types of Class 1 patients could involvelow frequency follow-up visits (1-2 visits/year), low frequency or noimaging, and less intense or no nodal assessments (ultrasound (US) scansversus computed tomography (CT) or nodal palpation in lieu of US or CT).Integration of the 40-GEP test suggests moderate intensity for 39.0%(40-GEP+AJCC) or 34.3% (40-GEP+BWH) of the cohort, and high intensitypatient management for 8.0% (FIG. 14). Moderate intensity managementcould allow for fewer follow-up visits relative to high intensitymanagement (2-4 versus 4-12 visits/year for 3 years), fewer invasiveprocedures (fewer biopsies and lymph node dissections), and more sparinguse of systemic and adjuvant therapy (immunotherapy, chemotherapy, oradjuvant radiation therapy) (FIG. 15). For those patients for whom theserisk-aligned recommendations suggest high intensity management, moreintensified surveillance and treatment modalities as shown in FIG. 15would be risk-appropriate.

The 40-GEP test results for a cohort of 300 NCCN-defined high-riskpatients were combined with T stage, and risk-aligned recommendationsfor patient management intensity were developed within the NCCNGuidelines® framework. This integration demonstrates the validated40-GEP prognostic test has clinical utility for complementing currentstaging systems and national patient guidelines to refine managementpathways for cSCC patients deemed high risk by clinicopathologicmethods. The 40-GEP test provides more accurate prediction of risk formetastasis in NCCN-defined high-risk cSCC patients, enabling improvedrisk-directed management decisions for therapy and surveillance. Thecurrent study reports the value of the test to identify within an NCCNhigh-risk cSCC patient population: 1) low-risk patients, havingmetastasis rates similar to rates of the general cSCC patientpopulation, and who could benefit from low intensity management; and 2)truly high-risk patients who may benefit from high intensity management.The value of more accurate prognosis would be an improvement in healthoutcomes through the delivery of risk-appropriate management.Collectively, the 40-GEP test provides independent probability for riskof metastasis that, in combination with AJCC or BWH T stage, couldimprove risk-directed management in patients diagnosed with NCCN-definedhigh-risk cSCC. In summary, integration of the 40-GEP test intomanagement of high-risk cSCC could enable net health outcomeimprovements for the majority of patients tested. The 40-GEP test can beintegrated within NCCN guideline recommendations and, in combinationwith T stage, may have clinical utility for impacting patient managementdecisions and outcomes.

All references cited in this application are expressly incorporated byreference herein.

1. A method for treating a patient with a cutaneous squamous cellcarcinoma (cSCC) tumor, the method comprising: (a) obtaining a diagnosisidentifying a risk of metastasis in a cSCC tumor sample from thepatient, wherein the diagnosis was obtained by: (1) determining theexpression level of 34 genes in a gene set; wherein the 34 genes in thegene set are: ACSBG1, ALOX12, APOBEC3G, ATP6VOE2, BBC3, BHLHB9, CEP76,DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896,LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1,RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, andZNF839; (2) comparing the expression levels of the 34 genes in the geneset from the cSCC tumor sample to the expression levels of the 34 genesin the gene set from a predictive training set to generate a probabilityscore of the risk of metastasis; (3) providing an indication as towhether the cSCC tumor has a low risk to a high risk of metastasis basedon the probability score generated in step (2); and (4) identifying thatthe cSCC tumor has a high risk of metastasis based on the probabilityscore and diagnosing the cSCC tumor as having a high risk of metastasis;and (b) administering to the patient an aggressive treatment when thedetermination is made in the affirmative that the patient has a cSCCtumor with a high risk of metastasis.
 2. The method of claim 1, furthercomprising performing a resection of the cSCC tumor when thedetermination is made in the affirmative that the patient has a cSCCtumor with a high risk of metastasis.
 3. The method of claim 1, whereinthe expression level of each gene in a gene set is determined by reversetranscribing the isolated mRNA and measuring a level of fluorescence foreach gene in the gene set by a nucleic acid sequence detection systemfollowing RT-PCR.
 4. The method of claim 1, wherein the cSCC tumorsample is obtained from a formalin-fixed, paraffin embedded sample. 5.The method of claim 1, wherein the probability score is between 0 and 1,and wherein a value of 1 indicates a higher probability of metastasisthan a value of
 0. 6. The method of claim 1, wherein the probabilityscore is a bimodal, two-Class analysis, wherein a patient having a valueof between 0 and 0.499 is designated as Class 1 (low risk) and a patienthaving a value of between 0.500 and 1.00 is designated as Class 2 (highrisk).
 7. The method of claim 1, wherein the probability score is atri-modal, three-Class analysis, wherein patients are designated asClass 1 (low risk), Class 2A (moderate risk), or Class 2B (high risk).8. The method of claim 1, wherein the gene set further comprises atleast one control gene, wherein the at least one control gene isselected from the group consisting of BAG6, KMT2D/MLL2, MDM2, FXR1,KMT2C, MDM4, VIM, and NF1B.
 9. The method of claim 8, wherein thecontrol genes are MDM2, KMT2D, BAG6, FXR1, MDM4, and KMT2C.
 10. A methodof treating a patient with a cutaneous squamous cell carcinoma (cSCC)tumor, the method comprising administering an aggressive cancertreatment regimen to the patient, wherein the patient has a cSCC tumorwith a moderate risk (Class 2A), or a high risk (Class 2B) as generatedby comparing the expression levels of 34 genes wherein the 34 genes areACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2,HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10,MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38,RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839, from thecSCC tumor with the expression levels of the same 34 genes ACSBG1,ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3,ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1,MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3,SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839 from a predictivetraining set.
 11. The method of claim 10, wherein the cSCC tumor isdetermined to have a low risk (Class 1), a moderate risk (Class 2A), ora high risk (Class 2B), wherein a patient having a low risk (Class 1)cSCC tumor has about a 0-10% risk for metastasis, a patient having amoderate risk (Class 2A) cSCC tumor has about a 10-49% risk formetastasis, and a patient having a high risk (Class 2B) cSCC tumor hasabout a 50-100% risk for metastasis.
 12. The method of claim 10, whereinthe gene set further comprises at least one control gene, wherein the atleast one control gene is selected from the group consisting of BAG6,KMT2D/MLL2, MDM2, FXR1, KMT2C, MDM4, VIM, and NF1B.
 13. The method ofclaim 12, wherein the control genes are MDM2, KMT2D, BAG6, FXR1, MDM4,and KMT2C. 14-37. (canceled)
 38. A method of determining one or moretreatment options for a patient with a cutaneous squamous cell carcinoma(cSCC) tumor, the method comprising: (a) identifying a risk ofmetastasis in a cSCC tumor sample from the patient, wherein the risk ofmetastasis was identified by: (1) determining the expression level of 34genes in a gene set; wherein the 34 genes in the gene set are: ACSBG1,ALOX12, APOBEC3G, ATP6VOE2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3,ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1,MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3,SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839; (2) comparingthe expression levels of the 34 genes in the gene set from the cSCCtumor sample to the expression levels of the 34 genes in the gene setfrom a predictive training set to identify the risk of metastasis andproviding an indication as to whether the cSCC tumor has a low risk(Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) ofmetastasis; and (b) determining that the patient receive a low intensitytreatment, a moderate intensity treatment, or a high intensity treatmentwhen the determination is made that the patient has a cSCC tumor with alow risk (Class 1), a moderate risk (Class 2A), or a high risk (Class2B) of metastasis, respectively.
 39. The method of claim 38, wherein thelow intensity treatment comprises one or more of: (a) clinical follow-upof one to two times per year; (b) reduced imaging or low frequency to noimaging; (c) reduced nodal assessment; and/or (d) no adjuvant treatment.40. The method of claim 38, wherein the moderate intensity treatmentcomprises one or more of: (a) clinical follow-up of two to four timesper year for about 3 years; (b) baseline and annual nodal imaging forabout 2 years; (c) consider a nodal biopsy or a neck dissection; and/or(d) consider an adjuvant treatment.
 41. The method of claim 38, whereinthe high intensity treatment comprises one or more of: (a) clinicalfollow-up of four to twelve times per year for about 3 years; (b)baseline and annual nodal imaging at least twice a year for about 2years; (c) recommend a nodal biopsy or a neck dissection; and/or (d)recommend an adjuvant treatment and/or a clinical trial.
 42. The methodof claim 38, further comprising performing a resection of the cSCC tumorwhen the determination is made in the affirmative that the patient has acSCC tumor with a moderate risk (Class 2A) or a high risk (Class 2B) ofmetastasis.
 43. The method of claim 38, wherein the expression level ofeach gene in a gene set is determined by reverse transcribing theisolated mRNA and measuring a level of fluorescence for each gene in thegene set by a nucleic acid sequence detection system following RT-PCR.44. The method of claim 38, wherein the cSCC tumor sample is obtainedfrom a formalin-fixed, paraffin embedded sample.
 45. The method of claim38, wherein the gene set further comprises at least one control gene,wherein the at least one control gene is selected from the groupconsisting of BAG6, KMT2D/MLL2, MDM2, FXR1, KMT2C, MDM4, VIM, and NF1B.46. The method of claim 45, wherein the control genes are MDM2, KMT2D,BAG6, FXR1, MDM4, and KMT2C.